kth.sePublications
Change search
Refine search result
1234567 51 - 100 of 1392
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 51.
    Amin, Saurabh
    et al.
    MIT, Cambridge, MA 02139 USA..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Preface to the Focused Issue on Dynamic Games in Cyber Security2019In: Dynamic Games and Applications, ISSN 2153-0785, E-ISSN 2153-0793, Vol. 9, no 4, p. 881-883Article in journal (Other academic)
  • 52.
    Andersson, Malin
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Aging sensitive battery control2022Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The battery is a component with significant impact on both the cost and environmental footprint of a full electric vehicle (EV). Consequently, there is a strong motivation to maximize its degree of utilization. Usage limits are enforced by the battery management system (BMS) to ensure safe operation and limit battery degradation. The limits tend to be conservative to account for uncertainty in battery state estimation as well as changes in the battery's characteristics due to aging. To improve the utilization degree, aging sensitive battery control is necessary. This refers to control that a) adjusts during the battery's life based on its state and b) balances the trade-off between utilization and degradation according to requirements from the specific application. 

    In state-of-the-art battery installations, only three signals are measured; current, voltage and temperature. However, the battery's behaviour is governed by other states that must be estimated such as its state-of-charge (SOC) or local concentrations and potentials. The BMS therefore relies on models to estimate states and to perform control actions. In order to realize points a) and b), the models that are used for state estimation and control must be updated onboard. An updated model can also serve the purpose of diagnosing the battery, since it reflects the changing properties of an aging battery. This thesis investigates identification of physics-based and empirical battery models from operational EV data. The work is divided into three main studies.

    1) A global sensitivity analysis was performed on the parameters of a high-order physics-based model. Measured current profiles from real EV:s were used as input and the parameters' impact on both modelled cell voltage and other internal states was assessed. The study revealed that in order to excite all model parameters, an input with high current rates, large SOC span and longer charge or discharge periods was required. This was only present in the data set from an electric truck with few battery packs. Data sets from vehicles with more packs (electric bus) and limited SOC operating window (plug-in hybrid truck) excited fewer model parameters.

    2) Empirical linear-parameter-varying (LPV) dynamic models were identified on driving data. Model parameters were formulated as functions of the measured temperature, current magnitude and estimated open circuit voltage (OCV). To handle the time-scale differences in battery voltage response, continuous-time system identification was employed. We concluded that the proposed models had superior predictive abilities compared to discrete and time-invariant counterparts. 

    3) Instead of using driving data to parametrize models, we also investigated the possibility to design the charging current in order to increase its information content about model parameters. This was formulated as an optimal control problem with charging speed and information content as objectives. To also take battery degradation into account, constraints on polarization was included. The results showed that parameter information can be increased without significant increase in charge time nor aging related stress.

    Download full text (pdf)
    andersson_lic
    Download full text (pdf)
    Errata
  • 53.
    Andersson, Malin
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Modelling, parameter identification and aging-sensitive management of lithium-ion batteries in heavy-duty electric vehicles2024Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The battery is a component with significant impact on both the cost and environmental footprint of a full electric vehicle (EV). Consequently, there is a strong motivation to maximize its degree of utilization. Usage limits are enforced by the battery management system (BMS) to ensure safe operation and limit battery degradation. The limits tend to be conservative to account for uncertainty in battery state estimation as well as changes in the battery's characteristics due to aging. To improve the utilization degree, aging-sensitive battery management is necessary. This refers to a management strategy that a) adjusts during the battery's life based on its state and b) balances the trade-off between utilization and degradation according to requirements from the specific application. 

    In state-of-the-art battery installations, only three signals are measured; current, voltage and temperature. However, the battery's behaviour is governed by other states that must be estimated such as its state-of-charge (SOC) or local concentrations and potentials. The BMS therefore relies on models to estimate states and to perform control actions. In order to realize points a) and b), the models that are used for state estimation and control must be updated onboard. An updated model can also serve the purpose of diagnosing the battery since it reflects the changing properties of an aging battery. This thesis investigates identification of electrochemical and empirical battery models from operational EV data. In addition, it studies model-based strategies for optimal and adaptive fast charging. The work is divided into four main studies.

    1) Empirical linear-parameter-varying (LPV) dynamic models were identified on driving data. Model parameters were formulated as functions of the measured temperature, current magnitude and estimated open circuit voltage (OCV). To handle the time-scale differences in battery voltage response, continuous-time system identification was employed. We concluded that the proposed models had superior predictive abilities compared to discrete and time-invariant counterparts.

    2) A global sensitivity analysis was performed on the parameters of a high-order electrochemical model. Measured current profiles from real EVs were used as input and the parameters' impact on both modelled cell voltage and other internal states was assessed. The study revealed that in order to excite all model parameters, an input with high current rates, large SOC span and longer charge or discharge periods was required. This was only present in the data set from an electric truck with few battery packs. Data sets from vehicles with more packs (electric bus) and limited SOC operating window (plug-in hybrid truck) excited fewer model parameters.

    3) Instead of using driving data to parametrize models, we also investigated the possibility to design the charging current in order to increase its information content about model parameters. This was formulated as an optimal experiment design problem in frequency domain. An aging-sensitive fast-charge procedure was optimized based on equivalent circuit model (ECM) states. Finally, different methods for combining the optimal fast charge and the optimal experiment were evaluated with regard to the resulting charging time and model performance.  

    4) Finally, aging-adaptive fast charging of automotive lithium-ion cells was studied. An electrochemical model was identified at the beginning of life and an electrochemically constrained fast charge was designed. The model parameters were then periodically re-evaluated during a cycling study and the charging procedure was updated to account for cell degradation. The study showed that adaptation of charge protocols increased the cell utilization compared to static protocols, but that heterogeneous degradation reduced the validity of the model and the adherence to electrochemical constraints.

    Download full text (pdf)
    fulltext
  • 54.
    Andersson, Malin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Klass, V. L.
    A Continuous-time LPV model for battery state-of-health estimation using real vehicle data2020In: CCTA 2020 - 4th IEEE Conference on Control Technology and Applications, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 692-698Conference paper (Refereed)
    Abstract [en]

    One approach for State-of-health estimation onboard electric vehicles is to train a data-driven virtual battery on operational data and use this model, rather than the actual battery, for performance tests. A temperature-dependent continuous-time output-error (OE) model is proposed as virtual battery and identified and validated on real operational data from electric buses. The proposed model is compared to discrete-time and parameter-invariant models and shows better performance on all data sets. In addition, the OE model structure is shown to be superior to a conventional Auto Regressive eXogenous (ARX) model for the purpose of modeling the battery voltage response. Finally, challenges regarding vehicle log data are identified and improvements to the model are suggested in order to capture observed un-modeled phenomena.

  • 55.
    Andersson, Malin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Scania CV AB, Granparksvagen 10, S-15148 Södertälje, Sweden..
    Streb, Moritz
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    Ko, Jing Ying
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    Klass, Verena Lofqvist
    Scania CV AB, Granparksvagen 10, S-15148 Södertälje, Sweden..
    Klett, Matilda
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry. Scania CV AB, Granparksvagen 10, S-15148 Södertälje, Sweden..
    Ekström, Henrik
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry. COMSOL AB, Tegnergatan 23, S-11140 Stockholm, Sweden..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Lindbergh, Göran
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    p Parametrization of physics-based battery models from input-output data: A review of methodology and current research2022In: Journal of Power Sources, ISSN 0378-7753, E-ISSN 1873-2755, Vol. 521, p. 230859-, article id 230859Article, review/survey (Refereed)
    Abstract [en]

    Physics-based battery models are important tools in battery research, development, and control. To obtain useful information from the models, accurate parametrization is essential. A complex model structure and many unknown and hard-to-measure parameters make parametrization challenging. Furthermore, numerous applications require non-invasive parametrization relying on parameter estimation from measurements of current and voltage. Parametrization of physics-based battery models from input-output data is a growing research area with many recent publications. This paper aims to bridge the gap between researchers from different fields that work with battery model parametrization, since successful parametrization requires both knowledge of the underlying physical system as well as understanding of theory and concepts behind parameter estimation. The review encompasses sensitivity analyses, methods for parameter optimization, structural and practical identifiability analyses, design of experiments and methods for validation as well as the use of machine learning in parametrization. We highlight that not all model parameters can accurately be identified nor are all relevant for model performance. Nonetheless, no consensus on parameter importance could be shown. Local methods are commonly chosen because of their computational advantages. However, we find that the implications of local methods for analysis of non-linear models are often not sufficiently considered in reviewed literature.

  • 56.
    Andersson, Malin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Streb, Moritz
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    Prathimala, Venu Gopal
    Siddiqui, Aamer
    Lodge, Andrew
    Löfqvist Klass, Verena
    Klett, Matilda
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Lindbergh, Göran
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Applied Electrochemistry.
    Electrochemical model-based aging-adaptive fast charging of automotive lithium-ion cellsManuscript (preprint) (Other academic)
    Abstract [en]

    Fast charging of electric vehicles remains a compromise between charging time and degradation penalty. Conventional battery management systems use experience-based charging protocols that are expected to meet vehicle lifetime goals. Novel electrochemical model-based battery fast charging uses a model to observe internal battery states. This enables control of charging rates based on states such as the lithium-plating potential but relies on an accurate model as well as accurate model parameters. However, the impact of battery degradation on the model’s accuracy and therefore the fitness of the estimated optimal charging procedure is often not considered. In this work, we therefore investigate electrochemical model-based aging-adaptive fast charging of automotive lithium-ion cells. First, an electrochemical model is identified at the beginning of life for 6 automotive prototype cells and the electrochemically constrained fast-charge is designed. The model parameters are then periodically re-evaluated during a cycling study and the charging procedure is updated to account for cell degradation. The proposed method is compared with two reference protocols to investigate both the effectiveness of selected electrochemical constraints as well as the benefit of aging-adaptive usage. Finally, post-mortem characterization is presented to highlight the benefit of aging-adaptive battery utilization.

  • 57. Andersson, O.
    et al.
    Doherty, P.
    Lager, M.
    Lindh, J. -O
    Persson, Linnea
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Topp, E. A.
    Tordenlid, J.
    Wahlberg, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    WARA-PS: a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation2021In: Autonomous Intelligent Systems, ISSN 2730-616X, Vol. 1, no 1, article id 9Article in journal (Refereed)
    Abstract [en]

    A research arena (WARA-PS) for sensing, data fusion, user interaction, planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented. The objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal challenges. The enabler is a computational infrastructure with a core system architecture for industrial and academic collaboration. This includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial vehicles. The motivating application for the demonstration is marine search and rescue operations. A state-of-art delegation framework for the mission planning together with three specific applications is also presented. The first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface vehicles. The second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles, and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine environments. The research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test facility. It would be most difficult to do experiments on this large scale without the WARA-PS research arena. Furthermore, these demonstrator activities have resulted in effective research dissemination with high public visibility, business impact and new research collaborations between academia and industry. 

  • 58.
    Andruetto, Claudia
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Pernestål Brenden, Anna
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Categorization of urban logistics concepts according to their sustainability performance2023In: 2022 Conference Proceedings Transport Research Arena, TRA Lisbon 2022, Elsevier BV , 2023, Vol. 72, p. 2708-2715Conference paper (Refereed)
    Abstract [en]

    The transport-related externalities of the urban logistics system impact the urban environment and the health of the citizens: there is a need to improve the sustainability of the system. In this paper, we use a framework for sustainability performance abessment and a literature review to analyse the urban logistics concepts of electrification, consolidation, cargo bikes and automation. In the literature, there is a focus on pollution, while a holistic perspective on sustainability is lacking. A Sustainability Performance Abessment (SPA) matrix is the main result of this paper, as a tool for comparing the concepts and understanding how they can be combined to achieve integrated benefits. To make informed decisions, stakeholders need knowledge from a holistic perspective. The findings presented in this paper are a first step to achieving this required knowledge.

  • 59. Ansari, R. Jaberzadeh
    et al.
    Karayiannidis, Yiannis
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Reducing the human effort for human-robot cooperative object manipulation via control design2017In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2017, Vol. 50, no 1, p. 14922-14927Conference paper (Refereed)
    Abstract [en]

    This study is concerned with the shared object manipulation problem in a physical Human-Robot Interaction (pHRI) setting. In such setups, the operator manipulates the object with the help of a robot. In this paper, the operator is assigned with the lead role, and the robot is passively following the forces/torques exerted by the operator. We propose a controller that is free from the well-known translation/rotation problem and enhances the operator's ability to move the object by reducing the human effort. The key point in our study is that the controller is defined based on the instantaneous center of rotation. The passivity of the system including the object and the manipulator has been evaluated. Simulation results validate the theoretical findings on different scenarios of subsequent rotations and translations of the object.

  • 60.
    Antonioli, Roberto P.
    et al.
    Wireless Telecom Research Group (GTEL), Federal University of Ceará, Fortaleza, Brazil.; Instituto Atlântico, Fortaleza, Brazil..
    Braga, Iran M.
    Wireless Telecom Research Group (GTEL), Federal University of Ceará, Fortaleza, Brazil..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Research, Stockholm, Sweden.
    Silva, Yuri C.B.
    Wireless Telecom Research Group (GTEL), Federal University of Ceará, Fortaleza, Brazil..
    Freitas, Walter C.
    Wireless Telecom Research Group (GTEL), Federal University of Ceará, Fortaleza, Brazil..
    Mixed Coherent and Non-Coherent Transmission for Multi-CPU Cell-Free Systems2023In: ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 1068-1073Conference paper (Refereed)
    Abstract [en]

    Existing works on cell-free systems consider either coherent or non-coherent downlink data transmission and a network deployment with a single central processing unit (CPU). While it is known that coherent transmission outperforms non-coherent transmission when assuming unlimited fronthaul links, the former requires a perfect timing synchronization, which is practically not viable over a large network. Furthermore, relying on a single CPU for geographically large cell-free networks is not scalable. Thus, to realize the expected gains of cell-free systems in practice, alternative transmission strategies for realistic multi-CPU cell-free systems are required. Therefore, this paper proposes a novel downlink data transmission scheme that combines and generalizes the existing coherent and non-coherent transmissions. The proposed transmission scheme, named mixed transmission, works based on the realistic assumption that only the access points (APs) controlled by a same CPU are synchronized, and thus transmit in a coherent fashion, while APs from different CPUs require no synchronism and transmit in a non-coherent manner. We also propose extensions of existing clustering algorithms for multi-CPU cell-free systems with mixed transmission. Simulation results show that the combination of the proposed clustering algorithms with mixed transmission have the potential to perform close to the ideal coherent transmission.

  • 61.
    Antonioli, Roberto P.
    et al.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440900 Fortaleza, Ceara, Brazil..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Soldati, Pablo
    Ericsson Res, Stand & Technol, S-16480 Stockholm, Sweden..
    Maciel, Tarcisio F.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440900 Fortaleza, Ceara, Brazil..
    User Scheduling for Sum-Rate Maximization Under Minimum Rate Constraints for the MIMO IBC2019In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 8, no 6, p. 1591-1595Article in journal (Refereed)
    Abstract [en]

    While the problem of sum-rate maximization of the multiple-input-multiple-output interference broadcast channel (MIMO IBC) has been extensively studied, most of the proposed solutions do not ensure a minimum rate for each scheduled user. In practice, many services require a minimum rate from the underlying communication links. Therefore, in this letter, we consider a sum-rate maximization problem with per-link minimum rate constraints for the MIMO IBC. The key idea is scheduling a suitable subset of the communication links for simultaneous transmissions, such that a minimum rate for each scheduled link can be ensured. To this end, we pose the sum-rate maximization problem as a combinatorial optimization problem, in which we introduce binary variables to the classical transceiver design problem. We propose a centralized solution based on branch-and-bound and a low-complexity semi-distributed scheme, in which a centralized unit is responsible for scheduling decisions, while the transceiver computations are distributed. Simulations show that the proposed solutions handle the user scheduling effectively, while the proposed semi-distributed scheme performs closely to the centralized scheme.

  • 62.
    Antonioli, Roberto Pinto
    et al.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
    Braga, Iran Mesquita
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Res, S-16480 Stockholm, Sweden..
    Silva, Yuri C. B.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
    de Almeida, Andre L. F.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
    Freitas, Walter C.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60455760 Fortaleza, Ceara, Brazil..
    On the Energy Efficiency of Cell-Free Systems With Limited Fronthauls: Is Coherent Transmission Always the Best Alternative?2022In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 21, no 10, p. 8729-8743Article in journal (Refereed)
    Abstract [en]

    Existing works concluded that coherent transmission outperforms non-coherent transmission in the downlink of cell-free systems when the fronthaul links have unlimited capacity. Since the capacity of the fronthaul links of cell-free networks is typically limited, in this paper we ask the question whether this conclusion holds under more realistic assumptions on the fronthaul capacity. To answer this question, we study and compare the performance of these transmission strategies by formulating novel energy efficiency (EE) maximization problems for both strategies, where we explicitly consider realistic fronthaul capacity and power consumption constraints. Despite the non-convexity of these problems, we derive closed-form equations to find suboptimal solutions of both problems using a unified framework that combines successive convex approximation and the Dinkelbach algorithm. Numerical results show that the performance of coherent transmission is severely impacted by limited fronthaul capacities, power consumption on the fronthaul links, user-centric cluster size and the number of antennas at the access points, such that in many cases non-coherent transmission achieves higher EE than coherent transmission. Based on these results, we provide deployment guidelines on when to use coherent or non-coherent transmission to maximize the EE of cell-free systems with limited fronthauls.

  • 63.
    Antonioli, Roberto Pinto
    et al.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440900 Fortaleza, Ceara, Brazil..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Res, Radio Dept, S-16480 Stockholm, Sweden..
    Soldati, Pablo
    Ericsson Res, Stand & Technol, S-16480 Stockholm, Sweden..
    Maciel, Tarcisio Ferreira
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440900 Fortaleza, Ceara, Brazil..
    Decentralized User Scheduling for Rate-Constrained Sum-Utility Maximization in the MIMO IBC2020In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 68, no 10, p. 6215-6229Article in journal (Refereed)
    Abstract [en]

    While the problems of sum-rate maximization and sum-power minimization subject to quality of service (QoS) constraints in the multiple input multiple output interference broadcast channel (MIMO IBC) have been widely studied, most of the proposed solutions have neglected the user scheduling aspect assuming that a feasible set of users has been previously selected. However, ensuring QoS for each user in the MIMO IBC involves the joint optimization of transmit/receive beamforming vectors, transmit powers, and user scheduling variables. To address the full problem, we propose a novel formulation of a rate-constrained sum-utility maximization problem which allows to either deactivate users or minimize the QoS degradation for some scheduled users in infeasible scenarios. Remarkably, this is achieved avoiding the complexity of traditional combinatorial formulations, but rather by introducing a novel expression of the QoS constraints that allows to solve the problem in a continuous domain. We propose centralized and decentralized solutions, where the decentralized solutions focus on practical design and low signaling overhead. The proposed solutions are then compared with benchmarking algorithms, where we show the effectiveness of the joint scheduling and transceiver design as well as the flexibility of the proposed solution performing advantageously in several MIMO IBC scenarios.

  • 64. Aragues, R.
    et al.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Intermittent connectivity maintenance with heterogeneous robots using a beads-on-a-ring strategy2019In: Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 120-126, article id 8814942Conference paper (Refereed)
    Abstract [en]

    We consider a scenario of cooperative task servicing, with a team of heterogeneous robots with different maximum speeds and communication radii, in charge of keeping the network intermittently connected. We abstract the task locations into a 1D cycle graph that is traversed by the communicating robots, and we discuss intermittent communication strategies so that each task location is periodically visited, with a worst-case revisiting time. Robots move forward and backward along the cycle graph, exchanging data with their previous and next neighbors when they meet, and updating their region boundaries. Asymptotically, each robot is in charge of a region of the cycle graph, depending on its capabilities. The method is distributed, and robots only exchange data when they meet.

  • 65. Aragues, Rosario
    et al.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Guallar, Pablo
    Sagues, Carlos
    Intermittent Connectivity Maintenance With Heterogeneous Robots2021In: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 37, no 1, p. 225-245Article in journal (Refereed)
    Abstract [en]

    In this article, we consider a scenario of cooperative task servicing, with a team of heterogeneous robots with different maximum speeds and communication radii, in charge of keeping the network intermittently connected. We abstract the task locations into a one-dimensional cycle graph that is traversed by the communicating robots, and we discuss intermittent communication strategies so that each task location is periodically visited, with a worst-case revisiting time. Robots move forward and backward along the cycle graph, exchanging data with their previous and next neighbors when they meet, and updating their region boundaries. Asymptotically, each robot is in charge of a region of the cycle graph, depending on its capabilities. The method is distributed, and robots only exchange data when they meet.

  • 66.
    Ardah, Khaled
    et al.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60020181 Fortaleza, Ceara, Brazil.;Tech Univ Ilmenau, Commun Res Lab, D-98693 Ilmenau, Germany..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Research.
    Silva, Yuri C. B.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60020181 Fortaleza, Ceara, Brazil..
    Freitas Jr, Walter C.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60020181 Fortaleza, Ceara, Brazil..
    de Almeida, Andre L. F.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, BR-60020181 Fortaleza, Ceara, Brazil..
    Hybrid Analog-Digital Beamforming Design for SE and EE Maximization in Massive MIMO Networks2020In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 69, no 1, p. 377-389Article in journal (Refereed)
    Abstract [en]

    Hybrid analog-digital (HAD) beamforming architectures have been proposed to facilitate the practical implementation of massive multiple-input multiple-output (MIMO) systems by reducing the number of employed radio frequency chains. While most prior studies have aimed to maximize spectral efficiency (SE), the present paper proposes a two-stage HAD beamforming design for multi-user MIMO systems that can be used to maximize either the system's overall energy efficiency (EE) or SE. This problem is nonconvex and NP-hard due to the joint optimization between the analog and digital domains and the constant modulus constraints required by the analog domain. To address this problem, we propose a decoupled two-stage design wherein the first stage, the analog beamforming parts are updated, which are then taken into account in the second stage to design the digital beamforming parts to maximize the system's EE or SE. We consider two widely-used HAD beamforming techniques that utilize either fully-connected (FC) or partially-connected (PC) architectures employing variable phase-shifters. Using the most recently available data for the circuitry power consumption of the components, we compare the performance of these two HAD architectures with that of the fully-digital (FD) architecture in terms of the total circuitry power consumption, and achieved SE and EE. We find that there is a certain number of users above which the FC architecture has higher circuitry power consumption than the FD counterpart, in contrast to the PC architecture that always has lower circuitry power consumption. More importantly, our results reveal, contrary to the common opinion, that depending on the circuitry parameters the FD architecture may achieve not only higher SE, but also higher EE than the HAD architectures.

  • 67.
    Ardah, Khaled
    et al.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440970 Fortaleza, Ceara, Brazil..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Res, Radio Dept, S-16480 Stockholm, Sweden.
    Silva, Yuri C. B.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440970 Fortaleza, Ceara, Brazil..
    Freitas, Walter C., Jr.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440970 Fortaleza, Ceara, Brazil..
    Cavalcanti, Francisco R. P.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60440970 Fortaleza, Ceara, Brazil..
    A Novel Cell Reconfiguration Technique for Dynamic TDD Wireless Networks2018In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, no 3, p. 320-323Article in journal (Refereed)
    Abstract [en]

    In dynamic time division duplexing (DTDD) systems, the uplink (UL) and downlink (DL) resources can be configured to adapt to changing traffic conditions. Therefiwe, DTDD systems are advantageously deployed in scenarios in which the UL and DL traffic demands are asymmetric and timevarying. Unfortunately, multicell DTDD systems give rise to base station-to-base station and user equipment-to-user equipment interference, that can severely degrade the system performance. Previous works on DTDD either assumed that the UL/DL configurations are given, or they did not take into account the negative impact of multicell DTDD interference. In this letter, we propose a novel cell reconfiguration technique that considers both the prevailing traffic conditions and multicell interference levels. The proposed technique is based on an efficient solution of a mixed integer linear program, whose objective is to maximize the overall system throughput taking into account users' traffic preferences. Realistic system level simulations indicate that the proposed scheme outperforms not only the static TDD system but also other reference schemes, that disregard the DTDD specific interference effects.

  • 68.
    Ardah, Khaled
    et al.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60020181 Fortaleza, Ceara, Brazil..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Res, SE-16480 Stockholm, Sweden.
    Silva, Yuri C. B.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60020181 Fortaleza, Ceara, Brazil..
    Freitas, Walter C., Jr.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60020181 Fortaleza, Ceara, Brazil..
    Cavalcanti, Francisco R. P.
    Univ Fed Ceara, Wireless Telecom Res Grp, BR-60020181 Fortaleza, Ceara, Brazil..
    A Unifying Design of Hybrid Beamforming Architectures Employing Phase Shifters or Switches2018In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 11, p. 11243-11247Article in journal (Refereed)
    Abstract [en]

    Hybrid beamfiorming (BF) architectures employing phase shifters or switches reduce the number of required radio frequency chains and the power consumption of base stations that employ a large number of antennas. Due to the inherent tradeoff between the number of radio frequency chains, the complexity of the employed analog and digital BF algorithms and the achieved spectral and energy efficiency, designing hybrid BF architectures is a complex task. To deal with this ormplexity, we propose a unifying design that is applicable to architectures employing either phase shifters or switches. In our design, the analog part (!if the hybrid BF architecture maximizes the capacity of the equivalent channel, while the digital part is updated using the well-known block diagonalizat' approach. We then employ the proposed joint analog-digital beamforming algorithm on lour recently proposed hybrid architectures and compare their performance in terms of spectral and energy efficiency, and find that the proposed analog-digital BF algorithm outperforms previously proposed schemes. We also find that phase shifterbased architectures achieve high spectral efficiency, whereas switching-based architectures can boost energy efficiency with increasing number of base station antennas.

  • 69.
    Ardah, Khaled
    et al.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, Fortaleza, Ceara, Brazil..
    Silva, Yuri C. B.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, Fortaleza, Ceara, Brazil..
    Freitas, Walter C., Jr.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, Fortaleza, Ceara, Brazil..
    Cavalcanti, Francisco R. P.
    Univ Fed Ceara, Wireless Telecom Res Grp GTEL, Fortaleza, Ceara, Brazil..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    An ADMM Approach to Distributed Coordinated Beamforming in Dynamic TDD Networks2017In: 2017 IEEE 7TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    We consider a dynamic time division duplexing wireless network and propose a distributed coordinated beamforming algorithm based on Alternating Direction Method of Multipliers (ADMM) technique assuming the availability of perfect channel state information. Our design objective is to minimize the sum transmit power at the base stations subject to minimum signal-to-interference-plus-noise ratio (SINR) constraints for downlink mobile stations and a maximum interference power threshold for uplink mobile stations. First, we propose a centralized algorithm based on the relaxed Semidefinite Programming (SDP) technique. To obtain the beamforming solution in a distributed way, we further propose a distributed coordinated beamforming algorithm using the ADMM technique. Detailed simulation results are presented to examine the effectiveness of the proposed algorithms. It is shown that the proposed algorithm achieves better performance in terms of the design objective and converges faster than the reference algorithm based on primal decomposition.

  • 70.
    Ariu, Kaito
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Inference and Online Learning in Structured Stochastic Systems2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis contributes to the field of stochastic online learning problems, with a collection of six papers each addressing unique aspects of online learning and inference problems under specific structures. The first four papers focus on exploration and inference problems, uncovering fundamental information-theoretic limits and efficient algorithms under various structures. The last two papers focus on maximizing rewards by efficiently leveraging these structures.

    The first paper addresses the complex problem of learning to cluster items based on binary user feedback for multiple questions. It establishes information-theoretical error lower bounds for both uniform and adaptive selection strategies under a fixed budget of rounds or users, and proposes an adaptive algorithm that efficiently allocates the budget.The second paper tackles the challenge of uncovering hidden communities in the Labeled Stochastic Block Model using single-shot observations of labels. It introduces a computationally efficient algorithm, Instance-Adaptive Clustering, which is the first to match instance-specific lower bounds on the expected number of misclassified items.The third paper delves into the best-arm identification or simple regret minimization problem within a Bayesian setting. It takes into consideration a prior distribution for the bandit problem and the expectation of simple regret with respect to that distribution, defining it as Bayesian simple regret.It characterizes the rate of Bayesian simple regret assuming certain continuity conditions on the prior, revealing that the leading term of Bayesian simple regret stems from parameters where the gap between optimal and suboptimal actions is less than . The fourth paper contributes to the fixed budget best-arm identification problem for two-arm bandits with Bernoulli rewards. It demonstrates the optimality of uniform sampling, which evenly samples the arms.It proves that no algorithm can outperform uniform sampling while being at least as good as uniform sampling for some bandit instances.The fifth paper revisits the regret minimization problem in sparse stochastic contextual linear bandits. It introduces a new algorithm, the Thresholded Lasso Bandit, which estimates the linear reward function and its sparse support, and then selects an arm based on these estimations. The algorithm achieves superior regret upper bounds compared to previous algorithms and numerically outperforms them.The sixth and final paper provides a theoretical analysis of recommendation systems in an online setting under unknown user-item preference probabilities and some structures. It derives regret lower bounds based on various structural assumptions and designs optimal algorithms that achieve these bounds. The analysis reveals the relative weights of the different components of regret, providing valuable insights into the efficient algorithms for online recommendation systems.

    This thesis addresses the technical challenge of structured stochastic online learning problems, providing new insights into the power and limitations of adaptivity in these problems.

    Download (pdf)
    summary
  • 71.
    Ariu, Kaito
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Online Dimensionality Reduction2021Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    In this thesis, we investigate online dimensionality reduction methods, wherethe algorithms learn by sequentially acquiring data. We focus on two specificalgorithm design problems in (i) recommender systems and (ii) heterogeneousclustering from binary user feedback. (i) For recommender systems, we consider a system consisting of m users and n items. In each round, a user,selected uniformly at random, arrives to the system and requests a recommendation. The algorithm observes the user id and recommends an itemfrom the item set. A notable restriction here is that the same item cannotbe recommended to the same user more than once, a constraint referred toas a no-repetition constraint. We study this problem as a variant of themulti-armed bandit problem and analyze regret with the various structurespertaining to items and users. We devise fundamental limits of regret andalgorithms that can achieve the limits order-wise. The analysis explicitlyhighlights the importance of each component of regret. For example, we candistinguish the regret due to the no-repetition constraint, that generated tolearn the statistics of user’s preference for an item, and that generated tolearn the low-dimensional space of the users and items were shown. (ii) Inthe clustering with binary feedback problem, the objective is to classify itemssolely based on limited user feedback. More precisely, users are just askedsimple questions with binary answers. A notable difficulty stems from theheterogeneity in the difficulty in classifying the various items (some itemsrequire more feedback to be classified than others). For this problem, wederive fundamental limits of the cluster recovery rates for both offline andonline algorithms. For the offline setting, we devise a simple algorithm thatachieves the limit order-wise. For the online setting, we propose an algorithm inspired by the lower bound. For both of the problems, we evaluatethe proposed algorithms by inspecting their theoretical guarantees and usingnumerical experiments performed on the synthetic and non-synthetic dataset.

    Download full text (pdf)
    fulltext
  • 72.
    Ariu, Kaito
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Cyberagent Inc, Tokyo, Japan..
    Abe, Kenshi
    Cyberagent Inc, Tokyo, Japan..
    Proutiere, Alexandre
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Thresholded Lasso Bandit2022In: International Conference On Machine Learning, Vol 162 / [ed] Chaudhuri, K Jegelka, S Song, L Szepesvari, C Niu, G Sabato, S, ML Research Press , 2022, p. 878-928Conference paper (Refereed)
    Abstract [en]

    In this paper, we revisit the regret minimization problem in sparse stochastic contextual linear bandits, where feature vectors may be of large dimension d, but where the reward function depends on a few, say s(0) << d, of these features only. We present Thresholded Lasso bandit, an algorithm that (i) estimates the vector defining the reward function as well as its sparse support, i.e., significant feature elements, using the Lasso framework with thresholding, and (ii) selects an arm greedily according to this estimate projected on its support. The algorithm does not require prior knowledge of the sparsity index s0 and can be parameter-free under some symmetric assumptions. For this simple algorithm, we establish non-asymptotic regret upper bounds scaling as O(log d+root T) in general, and as O(log d + log T) under the so-called margin condition (a probabilistic condition on the separation of the arm rewards). The regret of previous algorithms scales as O(log d+ root T log(dT)) and O(log T log d) in the two settings, respectively. Through numerical experiments, we confirm that our algorithm outperforms existing methods.

  • 73.
    Ariu, Kaito
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Kato, Masahiro
    Komiyama, Junpei
    McAlinn, Kenichiro
    Qin, Chao
    Policy Choice and Best Arm Identification: Asymptotic Analysis of Exploration SamplingManuscript (preprint) (Other academic)
  • 74.
    Ariu, Kaito
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Ok, Jungseul
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Proutiere, Alexandre
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Yun, Se-Young
    Optimal Clustering from Noisy Binary FeedbackManuscript (preprint) (Other academic)
    Abstract [en]

    We consider the problem of solving large-scale labeling tasks with minimal effort put on the users. Examples of such tasks include those in some of the recent CAPTCHA systems, where users clicks (binary answers) constitute the only data available to label images. Specifically, we study the generic problem of clustering a set of items from binary user feedback. Items are grouped into initially unknown non-overlapping clusters. To recover these clusters, the learner sequentially presents to users a finite list of items together with a question with a binary answer selected from a fixed finite set. For each of these items, the user provides a noisy answer whose expectation is determined by the item cluster and the question and by an item-specific parameter characterizing the {\it hardness} of classifying the item. The objective is to devise an algorithm with a minimal cluster recovery error rate. We derive problem-specific information-theoretical lower bounds on the error rate satisfied by any algorithm, for both uniform and adaptive (list, question) selection strategies. For uniform selection, we present a simple algorithm built upon the K-means algorithm and whose performance almost matches the fundamental limits. For adaptive selection, we develop an adaptive algorithm that is inspired by the derivation of the information-theoretical error lower bounds, and in turn allocates the budget in an efficient way. The algorithm learns to select items hard to cluster and relevant questions more often. We compare the performance of our algorithms with or without the adaptive selection strategy numerically and illustrate the gain achieved by being adaptive.

  • 75.
    Ariu, Kaito
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Proutiere, Alexandre
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Yun, Se-Young
    Instance-Optimal Cluster Recovery in the Labeled Stochastic Block ModelManuscript (preprint) (Other academic)
  • 76.
    Ariu, Kaito
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Ryu, Narae
    Yun, Se-Young
    Proutiere, Alexandre
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Regret in Online Recommendation Systems2020Conference paper (Refereed)
    Abstract [en]

    This paper proposes a theoretical analysis of recommendation systems in an online setting, where items are sequentially recommended to users over time. In each round, a user, randomly picked from a population of $m$ users, requests a recommendation. The decision-maker observes the user and selects an item from a catalogue of $n$ items. Importantly, an item cannot be recommended twice to the same user. The probabilities that a user likes each item are unknown. The performance of the recommendation algorithm is captured through its regret, considering as a reference an Oracle algorithm aware of these probabilities. We investigate various structural assumptions on these probabilities: we derive for each structure regret lower bounds, and devise algorithms achieving these limits. Interestingly, our analysis reveals the relative weights of the different components of regret: the component due to the constraint of not presenting the same item twice to the same user, that due to learning the chances users like items, and finally that arising when learning the underlying structure. 

  • 77.
    Ashraf, S. A.
    et al.
    Ericsson Research, Germany.
    Blasco, R.
    Ericsson Research, Finland.
    Do, H.
    Ericsson Research, Sweden.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Research, Sweden.
    Zhang, C.
    Ericsson Research, Germany.
    Sun, Wanlu
    Ericsson Research, Sweden.
    Supporting Vehicle-to-Everything Services by 5G New Radio Release-16 Systems2020In: IEEE Communications Standards Magazine, ISSN 2471-2825, Vol. 4, no 1, p. 26-32, article id 9088326Article in journal (Refereed)
    Abstract [en]

    Release-16 of the 5G New Radio (NR), developed by the 3rd Generation Partnership Project (3GPP), includes technology enablers for advanced vehicle-to-everything (V2X) communication services that go far beyond those offered by Long Term Evolution (LTE) systems. In particular, the Release-16 NR cellular interface and the NR sidelink interface are designed to enable platooning, advanced driving such as collision avoidance and cooperative lane change, extended sensors, and remote driving use cases. Compared to the LTE sidelink, the NR sidelink is equipped with a host of new capabilities including physical layer unicast and groupcast, reliable communication using feedback-based retransmissions, operation in millimeter-wave frequencies, advanced resource allocation, and quality of service management. In this article, we summarize the outcome of the related work carried out in 3GPP and discuss how the Release-16 NR capabilities can be used to provide advanced V2X services. We conclude by discussing next steps of the V2X service evolution and the NR sidelink capabilities.

  • 78.
    Assran, By Mahmoud
    et al.
    McGill Univ, Dept Elect & Comp Engn, Montreal, PQ H3A 0G4, Canada..
    Aytekin, Arda
    Ericsson AB, S-16440 Stockholm, Sweden..
    Feyzmahdavian, Hamid Reza
    ABB, S-72226 Stockholm, Sweden..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Rabbat, Michael G.
    Facebook Inc, Dept AI Res, Montreal, PQ H2S 3G9, Canada..
    Advances in Asynchronous Parallel and Distributed Optimization2020In: Proceedings of the IEEE, ISSN 0018-9219, E-ISSN 1558-2256, Vol. 108, no 11, p. 2013-2031Article in journal (Refereed)
    Abstract [en]

    Motivated by large-scale optimization problems arising in the context of machine learning, there have been several advances in the study of asynchronous parallel and distributed optimization methods during the past decade. Asynchronous methods do not require all processors to maintain a consistent view of the optimization variables. Consequently, they generally can make more efficient use of computational resources than synchronous methods, and they are not sensitive to issues like stragglers (i.e., slow nodes) and unreliable communication links. Mathematical modeling of asynchronous methods involves proper accounting of information delays, which makes their analysis challenging. This article reviews recent developments in the design and analysis of asynchronous optimization methods, covering both centralized methods, where all processors update a master copy of the optimization variables, and decentralized methods, where each processor maintains a local copy of the variables. The analysis provides insights into how the degree of asynchrony impacts convergence rates, especially in stochastic optimization methods.

  • 79.
    Aumayr, Erik
    et al.
    LM Ericsson, Network Management Res Lab, Athlone, Ireland..
    Feghhi, Saman
    LM Ericsson, Network Management Res Lab, Athlone, Ireland..
    Vannella, Filippo
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Res, Stockholm, Sweden.
    Al Hakim, Ezeddin
    Iakovidis, Grigorios
    KTH. Ericsson Res, Stockholm, Sweden.
    A Safe Reinforcement Learning Architecture for Antenna Tilt Optimisation2021In: 2021 Ieee 32Nd Annual International Symposium On Personal, Indoor And Mobile Radio Communications (PIMRC), Institute of Electrical and Electronics Engineers (IEEE) , 2021Conference paper (Refereed)
    Abstract [en]

    Safe interaction with the environment is one of the most challenging aspects of Reinforcement Learning (RL) when applied to real-world problems. This is particularly important when unsafe actions have a high or irreversible negative impact on the environment. In the context of network management operations, Remote Electrical Tilt (RET) optimisation is a safety-critical application in which exploratory modifications of antenna tilt angles of base stations can cause significant performance degradation in the network. In this paper, we propose a modular Safe Reinforcement Learning (SRL) architecture which is then used to address the RET optimisation in cellular networks. In this approach, a safety shield continuously benchmarks the performance of RL agents against safe baselines, and determines safe antenna tilt updates to be performed on the network. Our results demonstrate improved performance of the SRL agent over the baseline while ensuring the safety of the performed actions.

  • 80.
    Avgouleas, Ioannis
    et al.
    Ericsson Research, Stockholm, Sweden.
    Skillermark, Per
    Ericsson Research, Stockholm, Sweden.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Research, Stockholm, Sweden.
    Söder, Johan
    Ericsson Research, Stockholm, Sweden.
    Half-Duplex User Equipment Relaying Policies for Uplink Improvement in beyond 5G Networks2023In: 2023 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 323-328Conference paper (Refereed)
    Abstract [en]

    We consider a 5G cellular system, in which cellular user equipments (UEs) are willing to assist a cell-edge UE with a weak uplink (UL). We aim to improve the UL coverage as well as the end-to-end spectral and energy efficiency when the assisting UEs follow a group or multihop half-duplex relaying policy. Specifically, we study the UL performance under different distance-dependent fading conditions to understand when it is beneficial to use UE relaying. This question is motivated by recent advances in the Third Generation Partnership Project that suggests exploring the technology potential of physical layer groupcast and unicast over the sidelink for improving the UL coverage. Somewhat surprisingly, half-duplex UE relaying policies that exploit sidelink groupcast or unicast have not been thoroughly compared in the literature. System evaluations indicate that spectral efficiency can be improved over six times (compared to the case without relaying) with only two relaying UEs, while great energy efficiency gains are also achieved, provided that the time used for reception and transmission over the half-duplex relays is properly allocated. We also find that when relaying is beneficial, group and multihop relaying have their distinct advantages depending on the path loss exponent and the geometry of the system.

  • 81.
    Aytekin, Arda
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Asynchronous First-Order Algorithms for Large-Scale Optimization: Analysis and Implementation2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Developments in communication and data storage technologies have made large-scale data collection more accessible than ever. The transformation of this data into insight or decisions typically involves solving numerical optimization problems. As the data volumes increase, the optimization problems grow so large that they can no longer be solved on a single computer. This has created a strong interest in developing optimization algorithms that can be executed efficiently on multiple computing nodes in parallel. One way to achieve efficiency in parallel computations is to allow for asynchrony among nodes, which corresponds to making the nodes spend less time coordinating with each other and more time computing, possibly based on delayed information.  However, asynchrony in optimization algorithms runs the risk of otherwise convergent algorithms divergent, and convergence analysis of asynchronous algorithms is generally harder. In the thesis, we develop theory and tools to help understand and implement asynchronous optimization algorithms under time-varying, bounded information delay.

    In the first part, we analyze the convergence of different asynchronous optimization algorithms. We first propose a new approach for minimizing the average of a large number of smooth component functions. The algorithm uses delayed partial gradient information, and it covers delayed incremental gradient and delayed coordinate descent algorithms as special cases. We show that when the total loss function is strongly convex and the component functions have Lipschitz-continuous gradients, the algorithm has a linear convergence rate. The step size of the algorithm can be selected without knowing the bound on the delay, and still, guarantees convergence to within a predefined level of suboptimality. Then, we analyze two different variants of incremental gradient descent algorithms for regularized optimization problems.  In the first variant, asynchronous mini-batching, we consider solving regularized stochastic optimization problems with smooth loss functions. We show that the algorithm with time-varying step sizes achieves the best-known convergence rates under synchronous operation when (i) the feasible set is compact or (ii) the regularization function is strongly convex, and the feasible set is closed and convex. This means that the delays have an asymptotically negligible effect on the convergence, and we can expect speedups when using asynchronous computations. In the second variant, proximal incremental aggregated gradient, we show that when the objective function is strongly convex, the algorithm with a constant step size that depends on the maximum delay bound and the problem parameters converges globally linearly to the true optimum.

    In the second part, we first present POLO, an open-source C++ library that focuses on algorithm development. We use the policy-based design approach to decompose the proximal gradient algorithm family into its essential policies. This helps us handle combinatorially increasing design choices with linearly many tools, and generates highly efficient code with small footprint.  Together with its sister library in Julia, POLO.jl, our software framework helps optimization and machine-learning researchers to quickly prototype their ideas, benchmark them against the state-of-the-art, and ultimately deploy the algorithms on different computing platforms in just a few lines of code. Then, using the utilities of our software framework, we build a new, ``serverless'' executor for parallel Alternating Direction Method of Multipliers (ADMM) iterations. We use Amazon Web Services' Lambda functions as the computing nodes, and we observe speedups up to 256 workers and efficiencies above 70% up to 64 workers. These preliminary results suggest that serverless runtimes, together with their availability and elasticity, are promising candidates for scaling the performance of distributed optimization algorithms.

    Download full text (pdf)
    2019-Aytekin
  • 82.
    Aytekin, Arda
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Exploiting serverless runtimes for large-scale optimization2019In: 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), IEEE Computer Society, 2019, p. 499-501, article id 8814497Conference paper (Refereed)
    Abstract [en]

    Serverless runtimes provide efficient and cost-effective environments for scalable computations, thanks to their event-driven and elastic nature. So far, they have mostly been used for stateless, data parallel and sporadic computations. In this work, we propose exploiting serverless runtimes to solve generic, large-scale optimization problems. To this end, we implement a parallel optimization algorithm for solving a regularized logistic regression problem, and use AWS Lambda for the compute-intensive work. We show that relative speedups up to 256 workers and efficiencies above 70% up to 64 workers can be expected.

  • 83.
    B. da Silva Jr., Jose Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    How to Split UL/DL Antennas in Full-DuplexCellular Networks2018In: IEEE International Conference on Communication (ICC’18): ThirdWorkshop on Full-Duplex Communications for Future Wireless Networks, Kansas City, MO, USA: IEEE Communications Society, 2018Conference paper (Refereed)
    Abstract [en]

    To further improve the potential of full-duplex com-munications, networks may employ multiple antennas at thebase station or user equipment. To this end, networks thatemploy current radios usually deal with self-interference andmulti-user interference by beamforming techniques. Althoughprevious works investigated beamforming design to improvespectral efficiency, the fundamental question of how to split theantennas at a base station between uplink and downlink infull-duplex networks has not been investigated rigorously. Thispaper addresses this question by posing antenna splitting as abinary nonlinear optimization problem to minimize the sum meansquared error of the received data symbols. It is shown that thisis an NP-hard problem. This combinatorial problem is dealt withby equivalent formulations, iterative convex approximations, anda binary relaxation. The proposed algorithm is guaranteed toconverge to a stationary solution of the relaxed problem with muchsmaller complexity than exhaustive search. Numerical resultsindicate that the proposed solution is close to the optimal in bothhigh and low self-interference capable scenarios, while the usuallyassumed antenna splitting is far from optimal. For large numberof antennas, a simple antenna splitting is close to the proposedsolution. This reveals that the importance of antenna splittingdiminishes with the number of antennas.

  • 84. Bagloee, S. A.
    et al.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Asadi, M.
    A hybrid machine-learning and optimization method for contraflow design in post-disaster cases and traffic management scenarios2019In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 124, p. 67-81Article in journal (Refereed)
    Abstract [en]

    The growing number of man-made and natural disasters in recent years has made the disaster management a focal point of interest and research. To assist and streamline emergency evacuation, changing the directions of the roads (called contraflow, a traffic control measure) is proven to be an effective, quick and affordable scheme in the action list of the disaster management. The contraflow is computationally a challenging problem (known as NP-hard), hence developing an efficient method applicable to real-world and large-sized cases is a significant challenge in the literature. To cope with its complexities and to tailor to practical applications, a hybrid heuristic method based on a machine-learning model and bilevel optimization is developed. The idea is to try and test several contraflow scenarios providing a training dataset for a supervised learning (regression) model which is then used in an optimization framework to find a better scenario in an iterative process. This method is coded as a single computer program synchronized with GAMS (for optimization), MATLAB (for machine learning), EMME3 (for traffic simulation), MS-Access (for data storage) and MS-Excel (as an interface), and it is tested using a real dataset from Winnipeg, and Sioux-Falls as benchmarks. The algorithm managed to find globally optimal solutions for the Sioux-Falls example and improved accessibility to the dense and congested central areas of Winnipeg just by changing the direction of some roads.

  • 85.
    Bai, Ting
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Alexander
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Mårtensson, Jonas
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Approximate Dynamic Programming for Platoon Coordination under Hours-of-Service Regulations2022In: 2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 7663-7669Conference paper (Refereed)
    Abstract [en]

    Truck drivers are required to stop and rest with a certain regularity according to the driving and rest time regulations, also called Hours-of-Service (HoS) regulations. This paper studies the problem of optimally forming platoons when considering realistic HoS regulations. In our problem, trucks have fixed routes in a transportation network and can wait at hubs along their routes to form platoons with others while fulfilling the driving and rest time constraints. We propose a distributed decision-making scheme where each truck controls its waiting times at hubs based on the predicted schedules of others. The decoupling of trucks' decision-makings contributes to an approximate dynamic programming approach for platoon coordination under HoS regulations. Finally, we perform a simulation over the Swedish road network with one thousand trucks to evaluate the achieved platooning benefits under the HoS regulations in the European Union (EU). The simulation results show that, on average, trucks drive in platoons for 37 % of their routes if each truck is allowed to be delayed for 5 % of its total travel time. If trucks are not allowed to be delayed, they drive in platoons for 12 % of their routes.

  • 86.
    Bai, Ting
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Alexander
    KTH, School of Architecture and the Built Environment (ABE), Centres, Centre for Transport Studies, CTS. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Mårtensson, Jonas
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Event-Triggered Distributed Model Predictive Control for Platoon Coordination at Hubs in a Transport System2021In: 2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 1198-1204Conference paper (Refereed)
    Abstract [en]

    This paper considers the problem of hub-based platoon coordination for a large-scale transport system, where trucks have individual utility functions to optimize. An event-triggered distributed model predictive control method is proposed to solve the optimal scheduling of waiting times at hubs for individual trucks. In this distributed framework, trucks are allowed to decide their waiting times independently and only limited information is shared between trucks. Both the predicted reward gained from platooning and the predicted cost for waiting at hubs are included in each truck's utility function. The performance of the coordination method is demonstrated in a simulation with one hundred trucks over the Swedish road network.

  • 87.
    Bai, Ting
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Digital Futures.
    Johansson, Alexander
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. Digital Futures.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. Digital Futures.
    Mårtensson, Jonas
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Digital Futures.
    Large-Scale Multi-Fleet Platoon Coordination: A Dynamic Programming Approach2023In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 24, no 12, p. 14427-14442Article in journal (Refereed)
    Abstract [en]

    Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefits of platooning, efficient dispatching strategies that facilitate the platoon formations across fleets are required. This paper presents a distributed framework for addressing multi-fleet platoon coordination in large transportation networks, where each truck has a fixed route and aims to maximize its own fleet's platooning profit by scheduling its waiting times at hubs. The waiting time scheduling problem of individual trucks is formulated as a distributed optimal control problem with continuous decision space and a reward function that takes non-zero values only at discrete points. By suitably discretizing the decision and state spaces, we show that the problem can be solved exactly by dynamic programming, without loss of optimality. Finally, a realistic simulation study is conducted over the Swedish road network with 5,000 trucks to evaluate the profit and efficiency of the approach. The simulation study shows that, compared to single-fleet platooning, multi-fleet platooning provided by our method achieves around 15 times higher monetary profit and increases the CO2 emission reductions from 0.4% to 5.5%. In addition, it shows that the developed approach can be carried out in real-time and thus is suitable for platoon coordination in large transportation systems.

  • 88.
    Bai, Ting
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Alexander
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Li, S.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Mårtensson, Jonas
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    A Pricing Rule for Third-Party Platoon Coordination Service Provider2022In: ASCC 2022 - 2022 13th Asian Control Conference, Proceedings, Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 2344-2349Conference paper (Refereed)
    Abstract [en]

    We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

  • 89.
    Bai, Ting
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Li, Yuchao
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
    Mårtensson, Jonas
    KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Rollout-Based Charging Strategy for Electric Trucks With Hours-of-Service Regulations2023In: IEEE Control Systems Letters, E-ISSN 2475-1456, Vol. 7, p. 2167-2172Article in journal (Refereed)
    Abstract [en]

    Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and rest time regulations, known as hours-of-service (HoS) regulations. This letter studies the optimal charging problems of electric trucks with delivery deadlines under HoS constraints. We assume that a collection of charging and rest stations is given along a pre-planned route with known detours and that the problem data are deterministic. The goal is to minimize the total cost associated with the charging and rest decisions during the entire trip. This problem is formulated as a mixed integer program with bilinear constraints, resulting in a high computational load when applying exact solution approaches. To obtain real-time solutions, we develop a rollout-based approximate scheme, which scales linearly with the number of stations while offering solid performance guarantees. We perform simulation studies over the Swedish road network based on realistic truck data. The results show that our rollout-based approach provides near-optimal solutions to the problem in various conditions while cutting the computational time drastically.

  • 90.
    Baig, Mirza Uzair
    et al.
    Ericsson Research, Sweden.
    Vinogradova, Julia
    Ericsson Research, Finland.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). Ericsson Research, Sweden.
    Mollén, Christopher
    Ericsson Research, Sweden.
    Joint Communication and Sensing Beamforming for Passive Object Localization2023In: WSA and SCC 2023: 26th International ITG Workshop on Smart Antennas and 13th Conference on Systems, Communications, and Coding, VDE Verlag GmbH , 2023, p. 226-231Conference paper (Refereed)
    Abstract [en]

    Joint communication and sensing (JCAS) is a promising technology not only to reuse spectrum and hardware resources, but also to enhance existing communication and sensing services. Recognizing these benefits of JCAS systems, several previous papers have proposed transceiver architectures, beamforming algorithms and joint target search and channel estimation schemes that facilitate the integration of communication and sensing. Realizing that localization of passive mobile objects is vital in, for example, intelligent transportation systems, this work focuses on JCAS beamforming schemes for localization of such objects. Specifically, we propose a single beam and a multibeam scheme for localization of passive objects in the coverage area. We study the inherent trade-off between sensing and communication when using these two schemes, related to the number of time slots and the transmit energy and their impact on the angle estimation errors. The results show that, in general, spatial separation between the communication and sensing beams in the multibeam scheme gives better performance compared to the temporal separation between the sensing and communication beams in the single beam scheme, especially when the power allocated to sensing is low compared to the communication power.

  • 91. Balaghi I., M. H.
    et al.
    Antunes, D. J.
    Mamduhi, Mohammad Hossein
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hirche, S.
    An Optimal LQG Controller for Stochastic Event-triggered Scheduling over a Lossy Communication Network2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 23, p. 58-63Article in journal (Refereed)
    Abstract [en]

    We consider a networked control loop in which the sensors acquire partial state information and communicate to a remote controller through a lossy communication network. A scheduler, collocated with the sensors, decides to transmit a locally estimated state to the controller based on an event-triggered transmission policy with stochastic thresholds. Assuming that the local estimator either senses the communication channel or receives an ideal acknowledgment from the remote estimator, then the optimal control law can be shown to be a linear function of the conditional expectation of the state. However, the probability distribution of the state conditioned on the information available to the controller based on the mentioned transmission policy and network is not Gaussian, but rather described by a sum of Gaussians with an increasing number of terms at every time-step. We show that the optimal LQG control law can be determined without tracking this probability distribution for finding its expected value. Moreover, we establish that the stochastic event-triggered scheduler can be appropriately regulated in order to achieve a desired triggering probability at every time-step.

  • 92. Balaghi I., M. H.
    et al.
    Antunes, D.
    Mamduhi, Mohammad H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hirche, S.
    Decentralized LQ-Consistent Event-triggered Control over a Shared Contention-based Network2022In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 67, no 3, p. 1430-1437Article in journal (Refereed)
    Abstract [en]

    Consider a network of multiple independent stochas-tic linear systems where, for each system, a scheduler collocatedwith the sensors arbitrates data transmissions to a correspondingremote controller through a shared contention-based communi-cation network. While the systems are physically independent,their optimal controller design problems may, in general, becomecoupled, due to network contention, if the schedulers triggertransmissions based on state-dependent events. In this article wepropose a class of probabilistic admissible schedulers for whichthe optimal controllers, with respect to local standard LQG costs,have the certainty equivalence property and can still be determineddecentrally. Then, two subclasses of scheduling policies withinthis class are introduced; a non-event-based subclass, so calledpurely stochastic transmission (PST) policy, and an event-basedsubclass, both with easily adjustable triggering probabilities atevery time step. We then prove that, given a PST policy withgiven triggering probabilities and an associated closed-loop per-formance with optimal control law, we can find an event-basedscheduler from the proposed subclass and with the same trigger-ing probabilities for which the associated closed-loop performancewith optimal control law is strictly superior. Moreover, we showthat, for each closed-loop system, the optimal state estimatorsfor both scheduling policies follows a linear iteration. Finally, weprovide a method to regulate the triggering probabilities of theschedulers by maximizing a network utility function.

  • 93.
    Balaghi, M. Hadi I.
    et al.
    Eindhoven Univ Technol, Dept Mech Engn, Control Syst Technol Grp, Eindhoven, Netherlands..
    Antunes, Duarte J.
    Eindhoven Univ Technol, Dept Mech Engn, Control Syst Technol Grp, Eindhoven, Netherlands..
    Mamduhi, Mohammad H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hirche, Sandra
    Tech Univ Munich, Chair Informat Oriented Control, Munich, Germany..
    A Decentralized Consistent Policy for Event-triggered Control over a Shared Contention-based Network2018In: 2018 IEEE Conference on Decision and Control  (CDC), IEEE , 2018, p. 1719-1724Conference paper (Refereed)
    Abstract [en]

    We consider a network of several independent linear systems controlled over a shared communication network. Data transmissions pertaining to each control loop are arbitrated by a scheduler collocated with the plant's sensors that transmits the state information to the corresponding remote controller collocated with the plant's actuators. The shared communication channel is assumed to be operating based on a contention-based protocol, endowing the networked control system with desirable reconfigurable and scalable features. We propose a class of scheduling policies which admit a decentralized optimal control implementation and an event-triggered policy within this class which is shown to be consistent, i.e. it results in a better control performance for any linear system, measured by an average quadratic cost than its non-event-based counterpart.

  • 94.
    Baran, Robin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Tan, Xiao
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Várnai, Péter
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Yu, Pian
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Ahlberg, Sofie
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Guo, Meng
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Shaw Cortez, Wenceslao E.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    A ROS Package for Human-In-the-Loop Planning and Control under Linear Temporal Logic Tasks2021In: IEEE International Conference on Automation Science and Engineering, Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 2182-2187Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a ROS software package for planning and control of robotic systems with a human-in-the-Ioop focus. The software uses temporal logic specifications, specifically Linear Temporal Logic, for a language-based method to develop correct-by-design high level robot plans. The approach is structured to allow a human to adjust the high-level plan online. A human may also take control of the robot (in a low-level control fashion), but the software prevents the human from implementing dangerous behaviour that would violate the high-level task specification. Finally, the planner is able to learn human-preferred high-level tasks by tracking human low-level control inputs in an inverse learning framework. The proposed approach is demonstrated in a warehouse setting with multiple robot agents to showcase the efficacy of the proposed solution.

  • 95.
    Barbosa, Fernando S.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.
    Lindemann, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.
    Integrated motion planning and control under metric interval temporal logic specifications2019In: 2019 18th European Control Conference, ECC 2019, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 2042-2049, article id 8795925Conference paper (Refereed)
    Abstract [en]

    This paper proposes an approach that combines motion planning and hybrid feedback control design in order to find and follow trajectories fulfilling a given complex mission involving time constraints. We use Metric Interval Temporal Logic (MITL) as a rich and rigorous formalism to specify such missions. The solution builds on three main steps: (i) using sampling-based motion planning methods and the untimed version of the mission specification in the form of Zone automaton, we find a sequence of waypoints in the workspace; (ii) based on the clock zones from the satisfying run on the Zone automaton, we compute time-stamps at which these waypoints should be reached; and (iii) to control the system to connect two waypoints in the desired time, we design a low-level feedback controller leveraging Time-varying Control Barrier Functions. Illustrative simulation results are included.

  • 96.
    Barbosa, Fernando S.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.
    Lindemann, Lars
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.
    Provably safe control of Lagrangian systems in obstacle-scattered environments2020In: 2020 59th IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2020Conference paper (Refereed)
    Abstract [en]

    We propose a hybrid feedback control law that guarantees both safety and asymptotic stability for a class of Lagrangian systems in environments with obstacles. Rather than performing trajectory planning and implementing a trajectory-tracking feedback control law, our approach requires a sequence of locations in the environment (a path plan) and an abstraction of the obstacle-free space. The problem of following a path plan is then interpreted as a sequence of reach-avoid problems: the system is required to consecutively reach each location of the path plan while staying within safe regions. Obstacle-free ellipsoids are used as a way of defining such safe regions, each of which encloses two consecutive locations. Feasible Control Barrier Functions (CBFs) are created directly from geometric constraints, the ellipsoids, ensuring forward-invariance, and therefore safety. Reachability to each location is guaranteed by asymptotically stabilizing Control Lyapunov Functions (CLFs). Both CBFs and CLFs are then encoded into quadratic programs (QPs) without the need of relaxation variables. Furthermore, we also propose a switching mechanism that guarantees the control law is correct and well-defined even when transitioning between QPs. Simulations show the effectiveness of the proposed approach in two complex scenarios.

  • 97.
    Barreau, Matthieu
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Aguiar, Miguel
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Liu, John
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Physics-informed Learning for Identification and State Reconstruction of Traffic Density2021In: 2021 60thIEEE conference on decision and control (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 2653-2658Conference paper (Refereed)
    Abstract [en]

    We consider the problem of traffic density reconstruction using measurements from probe vehicles (PVs) with a low penetration rate. In other words, the number of sensors is small compared to the number of vehicles on the road. The model used assumes noisy measurements and a partially unknown first-order model. All these considerations make the use of machine learning to reconstruct the state the only applicable solution. We first investigate how the identification and reconstruction processes can be merged and how a sparse dataset can still enable a good identification. Secondly, we propose a pre-training procedure that aids the hyperparameter tuning, preventing the gradient descent algorithm from getting stuck at saddle points. Examples using numerical simulations and the SUMO traffic simulator show that the reconstructions are close to the real density in all cases.

  • 98.
    Barreau, Matthieu
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control). KTH Royal Inst Technol Stockholm, Div Decis & Control Syst, Stockholm, Sweden..
    Scherer, Carsten W.
    Univ Stuttgart, Dept Math, Stuttgart, Germany..
    Gouaisbaut, Frederic
    Univ Toulouse, LAAS, CNRS, UPS, Toulouse, France..
    Seuret, Alexandre
    Univ Toulouse, LAAS, CNRS, UPS, Toulouse, France..
    Integral Quadratic Constraints on Linear Infinite-dimensional Systems for Robust Stability Analysis2020In: Ifac papersonline, Elsevier BV , 2020, Vol. 53, no 2, p. 7752-7757Conference paper (Refereed)
    Abstract [en]

    This paper proposes a framework to assess the stability of an Ordinary Differential Equation (ODE) which is coupled to a 1D-partial differential equation (PDE). The stability theorem is based on a new result on Integral Quadratic Constraints (IQCs) and expressed in terms of two linear matrix inequalities with a moderate computational burden. The IQCs are not generated using dissipation inequalities involving the whole state of an infinite-dimensional system, but by using projection coefficients of the infinite-dimensional state. This permits to generalize our robustness result to many other PDEs. The proposed methodology is applied to a time-delay system and numerical results comparable to those in the literature are obtained. 

  • 99.
    Barreau, Matthieu
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Selivanov, A.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Dynamic Traffic Reconstruction using Probe Vehicles2020In: 2020 59th IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers Inc. , 2020, Vol. 2020, p. 233-238, article id 9304446Conference paper (Refereed)
    Abstract [en]

    This article deals with the observation problem in traffic flow theory. The model used is the quasiilinear viscous Burgers equation. Instead of using the traditional fixed sensors to estimate the state of the traffic at given points, the measurements here are obtained from Probe Vehicles (PVs). We propose then a moving dynamic boundary observer whose boundaries are defined by the trajectories of the PVs. The main result of this article is the exponential convergence of the observation error, and, in some cases, its finite-time convergence. Finally, numerical simulations show that it is possible to observe the traffic in the congested, free-flow, and mixed regimes provided that the number of PVs is large enough.

  • 100.
    Barreau, Matthieu
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Tarbouriech, Sophie
    Univ Toulouse, CNRS, LAAS, UPS, Toulouse, France..
    Gouaisbaut, Frederic
    Univ Toulouse, CNRS, LAAS, UPS, Toulouse, France..
    Lyapunov stability analysis of a mass-spring system subject to friction2021In: Systems & control letters (Print), ISSN 0167-6911, E-ISSN 1872-7956, Vol. 150, article id 104910Article in journal (Refereed)
    Abstract [en]

    This paper deals with the stability analysis of a mass-spring system subject to friction using Lyapunov-based arguments. As the described system presents a stick-slip phenomenon, the mass may then periodically stick to the ground. The objective consists of developing numerically tractable conditions ensuring the global asymptotic stability of the unique equilibrium point. The proposed approach merges two intermediate results: The first one relies on the characterization of an attractor around the origin, to which converges the closed-loop trajectories. The second result assesses the regional asymptotic stability of the equilibrium point by estimating its basin of attraction. The main result relies on conditions allowing to ensure that the attractor issued from the first result is included in the basin of attraction of the origin computed from the second result. An illustrative example draws the interest of the approach.

1234567 51 - 100 of 1392
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf