Change search
Refine search result
1234567 1 - 50 of 312
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • 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.
  • 1.
    Abdalmoaty, Mohamed
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH Royal Institute of Technology.
    Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions2019Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Data-driven modeling of stochastic nonlinear systems is recognized as a very challenging problem, even when reduced to a parameter estimation problem. A main difficulty is the intractability of the likelihood function, which renders favored estimation methods, such as the maximum likelihood method, analytically intractable. During the last decade, several numerical methods have been developed to approximately solve the maximum likelihood problem. A class of algorithms that attracted considerable attention is based on sequential Monte Carlo algorithms (also known as particle filters/smoothers) and particle Markov chain Monte Carlo algorithms. These algorithms were able to obtain impressive results on several challenging benchmark problems; however, their application is so far limited to cases where fundamental limitations, such as the sample impoverishment and path degeneracy problems, can be avoided.

    This thesis introduces relatively simple alternative parameter estimation methods that may be used for fairly general stochastic nonlinear dynamical models. They are based on one-step-ahead predictors that are linear in the observed outputs and do not require the computations of the likelihood function. Therefore, the resulting estimators are relatively easy to compute and may be highly competitive in this regard: they are in fact defined by analytically tractable objective functions in several relevant cases. In cases where the predictors are analytically intractable due to the complexity of the model, it is possible to resort to {plain} Monte Carlo approximations. Under certain assumptions on the data and some conditions on the model, the convergence and consistency of the estimators can be established. Several numerical simulation examples and a recent real-data benchmark problem demonstrate a good performance of the proposed method, in several cases that are considered challenging, with a considerable reduction in computational time in comparison with state-of-the-art sequential Monte Carlo implementations of the ML estimator.

    Moreover, we provide some insight into the asymptotic properties of the proposed methods. We show that the accuracy of the estimators depends on the model parameterization and the shape of the unknown distribution of the outputs (via the third and fourth moments). In particular, it is shown that when the model is non-Gaussian, a prediction error method based on the Gaussian assumption is not necessarily more accurate than one based on an optimally weighted parameter-independent quadratic norm. Therefore, it is generally not obvious which method should be used. This result comes in contrast to a current belief in some of the literature on the subject. 

    Furthermore, we introduce the estimating functions approach, which was mainly developed in the statistics literature, as a generalization of the maximum likelihood and prediction error methods. We show how it may be used to systematically define optimal estimators, within a predefined class, using only a partial specification of the probabilistic model. Unless the model is Gaussian, this leads to estimators that are asymptotically uniformly more accurate than linear prediction error methods when quadratic criteria are used. Convergence and consistency are established under standard regularity and identifiability assumptions akin to those of prediction error methods.

    Finally, we consider the problem of closed-loop identification when the system is stochastic and nonlinear. A couple of scenarios given by the assumptions on the disturbances, the measurement noise and the knowledge of the feedback mechanism are considered. They include a challenging case where the feedback mechanism is completely unknown to the user. Our methods can be regarded as generalizations of some classical closed-loop identification approaches for the linear time-invariant case. We provide an asymptotic analysis of the methods, and demonstrate their properties in a simulation example.

  • 2.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem⁎2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 784-789Article in journal (Refereed)
    Abstract [en]

    The estimation problem of stochastic Wiener-Hammerstein models is recognized to be challenging, mainly due to the analytical intractability of the likelihood function. In this contribution, we apply a computationally attractive prediction error method estimator to a real-data stochastic Wiener-Hammerstein benchmark problem. The estimator is defined using a deterministic predictor that is nonlinear in the input. The prediction error method results in tractable expressions, and Monte Carlo approximations are not necessary. This allows us to tackle several issues considered challenging from the perspective of the current mainstream approach. Under mild conditions, the estimator can be shown to be consistent and asymptotically normal. The results of the method applied to the benchmark data are presented and discussed.

  • 3.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors2018Conference paper (Refereed)
  • 4.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Linear Prediction Error Methods for Stochastic Nonlinear Models2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 105, p. 49-63Article in journal (Refereed)
    Abstract [en]

    The estimation problem for stochastic parametric nonlinear dynamical models is recognized to be challenging. The main difficulty is the intractability of the likelihood function and the optimal one-step ahead predictor. In this paper, we present relatively simple prediction error methods based on non-stationary predictors that are linear in the outputs. They can be seen as extensions of the linear identification methods for the case where the hypothesized model is stochastic and nonlinear. The resulting estimators are defined by analytically tractable objective functions in several common cases. It is shown that, under certain identifiability and standard regularity conditions, the estimators are consistent and asymptotically normal. We discuss the relationship between the suggested estimators and those based on second-order equivalent models as well as the maximum likelihood method. The paper is concluded with a numerical simulation example as well as a real-data benchmark problem.

    The full text will be freely available from 2021-04-01 16:05
  • 5.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Identification of a Class of Nonlinear Dynamical Networks⁎2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 868-873Article in journal (Refereed)
    Abstract [en]

    Identification of dynamic networks has attracted considerable interest recently. So far the main focus has been on linear time-invariant networks. Meanwhile, most real-life systems exhibit nonlinear behaviors; consider, for example, two stochastic linear time-invariant systems connected in series, each of which has a nonlinearity at its output. The estimation problem in this case is recognized to be challenging, due to the analytical intractability of both the likelihood function and the optimal one-step ahead predictors of the measured nodes. In this contribution, we introduce a relatively simple prediction error method that may be used for the estimation of nonlinear dynamical networks. The estimator is defined using a deterministic predictor that is nonlinear in the known signals. The estimation problem can be defined using closed-form analytical expressions in several non-trivial cases, and Monte Carlo approximations are not necessarily required. We show, that this is the case for some block-oriented networks with no feedback loops and where all the nonlinear modules are polynomials. Consequently, the proposed method can be applied in situations considered challenging by current approaches. The performance of the estimation method is illustrated on a numerical simulation example.

  • 6.
    Abrardo, Andrea
    et al.
    Univ Siena, Dipartimento Ingn Informaz, I-53100 Siena, Italy. brardo, Andrea; Moretti, Marco.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Moretti, Marco
    Distributed Digital and Hybrid Beamforming Schemes With MMSE-SIC Receivers for the MIMO Interference Channel2019In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 68, no 7, p. 6790-6804Article in journal (Refereed)
    Abstract [en]

    This paper addresses the problem of weighted sumrate maximization and mean squared error (MSE) minimization for the multiple-input multiple-output (MIMO) interference channel. Specifically, we consider a weighted minimum MSE architecture where each receiver employs successive interference cancellation (SIC) to separate the various received data streams and derive a hybrid beamforming scheme, where the transmitters operate with a number of radio frequency chains smaller than the number of antennas, particularly suited for millimeter-wave channels and 5G applications. To derive our proposed schemes, we first study the relationship between sum-rate maximization and weighted MSE minimization when using SIC receivers, assuming fully digital beamforming. Next, we consider the important-and, as it turns out, highly non-trivial-case where the transmitters employ hybrid digital/analog beamforming, developing a distributed joint hybrid precoding and SIC-based combining algorithm. Moreover, for practical implementation, we propose a signaling scheme that utilizes a common broadcast channel and facilitates the acquisition of channel state information, assuming minimal assistance from a central node such as a cellular base station. Numerical results show that both the proposed weighted MMSE-SIC schemes exhibit great advantages with respect to their linear counterparts in terms of complexity, feedback information, and performance.

  • 7.
    Abrardo, Andrea
    et al.
    Univ Siena, Dipartimento Ingn Informaz, I-53100 Siena, Italy..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Moretti, Marco
    Univ Pisa, Dipartimento Ingn Informaz, I-50126 Pisa, Italy..
    Telek, Miklos
    Budapest Univ Technol & Econ, Dept Networked Syst & Serv, H-1117 Budapest, Hungary.;MTA BME Informat Syst Res Grp, H-1117 Budapest, Hungary..
    MMSE Receiver Design and SINR Calculation in MU-MIMO Systems With Imperfect CSI2019In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 8, no 1, p. 269-272Article in journal (Refereed)
    Abstract [en]

    The performance of the uplink of multiuser multiple input multiple output systems depends critically on the receiver architecture and on the quality of the acquired channel state information. A popular approach is to design linear receivers that minimize the mean squared error (MSE) of the received data symbols. Unfortunately, most of the literature does not take into account the presence of channel state information errors in the MSE minimization. In this letter we develop a linear minimum MSE (MMSE) receiver that employs the noisy instantaneous channel estimates to minimize the MSE, and highlight the dependence of the receiver performance on the pilot-to-data power ratio. By invoking the theory of random matrices, we calculate the users' signal-to-interference-plus-noise ratio as a function of the number of antennas and the pilot-to-data power ratio of all users. Numerical results indicate that this new linear receiver outperforms the classical mismatched MMSE receiver.

  • 8.
    Adaldo, Antonio
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Event-triggered and cloud-support control of multi-robot systems2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In control of multi-robot systems, the aim is to obtain a coordinated behavior through local interactions among the robots. A multi-agent system is an abstract model of a multi-robot system. In this thesis, we investigate multi-agent systems where inter-agent communication is modeled by discrete events triggered by conditions on the internal state of the agents. We consider two models of communication. In the first model, two agents exchange information directly with each other. In the second model, all information is exchanged asynchronously over a shared repository. Four contributions on control algorithms for multi-agent systems are offered in the thesis. The first contribution is an event-triggered pinning control algorithm for a network of agents with nonlinear dynamics and time-varying topology. Pinning control is a strategy to steer the behavior of the system in a desired manner by controlling only a small fraction of the agents. We express the controllability of the network in terms of an average value of the network connectivity over time, and we show that all the agents can be driven to a desired reference trajectory. The second contribution is a control algorithm for multi-agent systems where inter-agent communication is substituted with a shared remote repository hosted on a cloud. The communication between each agent and the cloud is modeled as a sequence of events scheduled recursively by the agent. We quantify the connectivity of the network and we show that it is possible to synchronize the multi-agent system to the same state trajectory, while guaranteeing that two consecutive cloud accesses by the same agent are separated by a lower-bounded time interval. The third contribution is a family of distributed controllers for coverage and surveillance tasks with a network of mobile agents with anisotropic sensing patterns. We develop an abstract model of the environment under inspection and define a measure of the coverage attained by the sensor network. We show that the network attains nondecreasing coverage, and we characterize the equilibrium configurations of the network. The fourth contribution is a distributed, cloud-supported control algorithm for inspection of 3D structures with a network of mobile sensing agents, similar to those considered in the third contribution. We develop an abstract model of the structure to inspect and quantify the degree of completion of the inspection. We demonstrate that, under the proposed algorithm, the network is guaranteed to complete the inspection in finite time. All results presented in the thesis are corroborated by numerical simulations and sometimes by experiments with aerial robotic platforms. The experiments show that the theory and methods developed in the thesis are of practical relevance.

  • 9.
    Adaldo, Antonio
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Cloud-supported effective coverage of 3D structures2018In: 2018 European Control Conference, ECC 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 95-100, article id 8550377Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a distributed algorithm for cloud-supported effective coverage of 3D structures with a network of sensing agents. The structure to inspect is abstracted into a set of landmarks, where each landmark represents a point or small area of interest, and incorporates information about position and orientation. The agents navigate the environment following the proposed control algorithm until all landmarks have reached a satisfactory level of coverage. The agents do not communicate with each other directly, but exchange data through a shared cloud repository which is accessed asynchronously and intermittently. We show formally that, under the proposed control architecture, the networked agents complete the coverage mission in finite time. The results are corroborated by simulations in ROS, and experimental evaluation is in progress.

  • 10.
    Adaldo, Antonio
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Liuzza, Davide
    Univ Sannio, Dept Engn, I-82100 Benevento, Italy..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Cloud-Supported Formation Control of Second-Order Multiagent Systems2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 4, p. 1563-1574Article in journal (Refereed)
    Abstract [en]

    This paper addresses a formation problem for a network of autonomous agents with second-order dynamics and bounded disturbances. Coordination is achieved by having the agents asynchronously upload (download) data to (from) a shared repository, rather than directly exchanging data with other agents. Well-posedness of the closed-loop system is demonstrated by showing that there exists a lower bound for the time interval between two consecutive agent accesses to the repository. Numerical simulations corroborate the theoretical results.

  • 11.
    Ahlberg, Sofie
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Human-in-the-Loop Control Synthesis for Multi-Agent Systems under Metric Interval Temporal Logic Specifications2019Licentiate thesis, monograph (Other academic)
    Abstract [en]

    With the increase of robotic presence in our homes and work environment, it has become imperative to consider human-in-the-loop systems when designing robotic controllers. This includes both a physical presence of humans as well as interaction on a decision and control level. One important aspect of this is to design controllers which are guaranteed to satisfy specified safety constraints. At the same time we must minimize the risk of not finding solutions, which would force the system to stop. This require some room for relaxation to be put on the specifications. Another aspect is to design the system to be adaptive to the human and its environment.

    In this thesis we approach the problem by considering control synthesis for multi-agent systems under hard and soft constraints, where the human has direct impact on how the soft constraint is violated. To handle the multi-agent structure we consider both a classical centralized automata based framework and a decentralized approach with collision avoidance. To handle soft constraints we introduce a novel metric; hybrid distance, which quantify the violation. The hybrid distance consists of two types of violation; continuous distance or missing deadlines, and discrete distance or spacial violation. These distances are weighed against each other with a weight constant we will denote as the human preference constant. For the human impact we consider two types of feedback; direct feedback on the violation in the form of determining the human preference constant, and direct control input through mixed-initiative control where the human preference constant is determined through an inverse reinforcement learning algorithm based on the suggested and followed paths. The methods are validated through simulations.

  • 12.
    Ahlén, Anders
    et al.
    Uppsala Univ, Signal Proc, Uppsala, Sweden.;Univ Newcastle, Dept Elect & Comp Engn, Callaghan, NSW, Australia..
    Åkerberg, Johan
    ABB Corp, Vasteras, Sweden..
    Eriksson, Markus
    Scania CV, Sodertalje, Sweden..
    Isaksson, Alf J.
    Linkoping Univ, Linkoping, Sweden.;Univ Newcastle, Callaghan, NSW, Australia.;Royal Inst Technol, Stockholm, Sweden.;ABB Corp Res, Vasteras, Sweden..
    Iwaki, Takuya
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligenta system, Decision and Control Systems (Automatic Control). JGC Corp, Yokohama, Kanagawa, Japan.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligenta system, Decision and Control Systems (Automatic Control).
    Knorn, Steffi
    Univ Newcastle, Ctr Complex Dynam Syst & Control, Callaghan, NSW, Australia.;Uppsala Univ, Signals & Syst Div, Uppsala, Sweden..
    Lindh, Thomas
    Iggesund Mill, Maintenance Technol Dev, Iggesund Paperboard, Sweden..
    Sandberg, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligenta system, Decision and Control Systems (Automatic Control). CALTECH, Pasadena, CA 91125 USA.;MIT, Lab Informat & Decis Syst, 77 Massachusetts Ave, Cambridge, MA 02139 USA..
    Toward Wireless Control in Industrial Process Automation: A Case Study at a Paper Mill2019In: IEEE Control Systems Magazine, ISSN 1066-033X, Vol. 39, no 5, p. 36-57Article in journal (Refereed)
    Abstract [en]

    Wireless sensors and networks are used only occasionally in current control loops in the process industry. With rapid developments in embedded and highperformance computing, wireless communication, and cloud technology, drastic changes in the architecture and operation of industrial automation systems seem more likely than ever. These changes are driven by ever-growing demands on production quality and flexibility. However, as discussed in "Summary," there are several research obstacles to overcome. The radio communication environment in the process industry is often troublesome, as the environment is frequently cluttered with large metal objects, moving machines and vehicles, and processes emitting radio disturbances [1], [2]. The successful deployment of a wireless control system in such an environment requires careful design of communication links and network protocols as well as robust and reconfigurable control algorithms.

  • 13.
    Aleksandrauskaite, Ruth
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Analysis of Velocity Estimation Methods for High-Performance Motion Control Systems2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The majority of all commercial electronics hardware is manufactured usingSurface Mount Technology (SMT). Nevertheless, the increased complexityand miniaturization of electronics impose tough performance requirementson the automation process.The research in this paper concerns test and analysis of alternative velocityestimation methods for high-performance embedded motion control systems.The motion system in Mycronic’s pick and place machines is regulated by amotion controller consisting of a feedforward component and a feedback controller.The linear displacement is measured with an incremental encoder andthe velocity is estimated with a state observer. Previous work suggests thatthe velocity estimation is inadequate.Different observer designs including state and disturbance estimators weretested and evaluated through simulations in MATLAB SIMULINKr. Afterthat, experiments were performed on a conveyor retrieved from a pick andplace machine.The results show that a Kalman filter is the best state estimator. However,the method requires extensive tuning to attain good performance. The trackingperformance and robustness of the motion control system was highly improvedwhen using a Perturbation observer with Kalman filtering. Nonetheless,the settling time for point-to-point movements was somewhat shorterwhen using a Kalman filter alone.

  • 14.
    Alinia, Bahram
    et al.
    Telecom SudParis, Inst Mines Telecom, F-91000 Evry, France. alebi, Mohammad Sadegh.
    Talebi Mazraeh Shahi, Mohammad Sadegh
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hajiesmaili, Mohammad H.
    Yekkehkhany, Ali
    Crespi, Noel
    Competitive Online Scheduling Algorithms with Applications in Deadline-Constrained EV Charging2018In: 2018 IEEE/ACM 26th International Symposium on Quality of Service, IWQoS 2018, IEEE, 2018, article id 8624184Conference paper (Refereed)
    Abstract [en]

    This paper studies the classical problem of online scheduling of deadline-sensitive jobs with partial values and investigates its extension to Electric Vehicle (EV) charging scheduling by taking into account the processing rate limit of jobs and charging station capacity constraint. The problem lies in the category of time-coupled online scheduling problems without availability of future information. This paper proposes two online algorithms, both of which are shown to be (2-\frac{1}{U})-competitive, where U is the maximum scarcity level, a parameter that indicates demand-to-supply ratio. The first proposed algorithm is deterministic, whereas the second is randomized and enjoys a lower computational complexity. When U grows large, the performance of both algorithms approaches that of the state-of-the-art for the case where there is processing rate limits on the jobs. Nonetheless in realistic cases, where U is typically small, the proposed algorithms enjoy a much lower competitive ratio. To carry out the competitive analysis of our algorithms, we present a proof technique, which is novel to the best of our knowledge. This technique could also be used to simplify the competitive analysis of some existing algorithms, and thus could be of independent interest.

  • 15.
    Alistarh, Dan
    et al.
    IST Austria, Klosterneuburg, Austria..
    Hoefler, Torsten
    Swiss Fed Inst Technol, Zurich, Switzerland..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Khirirat, Sarit
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Konstantinov, Nikola
    IST Austria, Klosterneuburg, Austria..
    Renggli, Cedric
    Swiss Fed Inst Technol, Zurich, Switzerland..
    The Convergence of Sparsified Gradient Methods2018In: Advances in Neural Information Processing Systems 31 (NIPS 2018) / [ed] Bengio, S Wallach, H Larochelle, H Grauman, K CesaBianchi, N Garnett, R, Neural Information Processing Systems (NIPS) , 2018, Vol. 31Conference paper (Refereed)
    Abstract [en]

    Stochastic Gradient Descent (SGD) has become the standard tool for distributed training of massive machine learning models, in particular deep neural networks. Several families of communication-reduction methods, such as quantization, large-batch methods, and gradient sparsification, have been proposed to reduce the overheads of distribution. To date, gradient sparsification methods-where each node sorts gradients by magnitude, and only communicates a subset of the components, accumulating the rest locally-are known to yield some of the largest practical gains. Such methods can reduce the amount of communication per step by up to three orders of magnitude, while preserving model accuracy. Yet, this family of methods currently has no theoretical justification. This is the question we address in this paper. We prove that, under analytic assumptions, sparsifying gradients by magnitude with local error correction provides convergence guarantees, for both convex and non-convex smooth objectives, for data-parallel SGD. The main insight is that sparsification methods implicitly maintain bounds on the maximum impact of stale updates, thanks to selection by magnitude. Our analysis also reveals that these methods do require analytical conditions to converge well, justifying and complementing existing heuristics.

  • 16.
    Andersson, Sofie
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Human in the Loop Least Violating Robot Control Synthesis under Metric Interval Temporal Logic Specifications2018In: 2018 European Control Conference, ECC 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 453-458, article id 8550179Conference paper (Refereed)
    Abstract [en]

    Recently, multiple frameworks for control synthesis under temporal logic have been suggested. The frameworks allow a user to give one or a set of robots high level tasks of different properties (e.g. temporal, time limited, individual and cooperative). However, the issue of how to handle tasks, which either seem to be or are infeasible, remains unsolved. In this paper we introduce a human to the loop, using the human's feedback to determine preference towards different types of violations of the tasks. We introduce a metric of violation called hybrid distance. We also suggest a novel framework for synthesizing a least violating controller with respect to the hybrid distance and the human feedback. Simulation result indicate that the suggested framework gives reasonable estimates of the metric, and that the suggested plans correspond to the expected ones.

  • 17. Ansari, R. Jaberzadeh
    et al.
    Karayiannidis, Yiannis
    KTH, School of Electrical Engineering and Computer Science (EECS), 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.

  • 18. Aragues, R.
    et al.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), 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.

  • 19.
    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), 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.

  • 20.
    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), 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.

  • 21.
    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), 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.

  • 22.
    Aytekin, Arda
    KTH, School of Electrical Engineering and Computer Science (EECS), 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.

  • 23.
    Aytekin, Arda
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), 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.

  • 24.
    B. da Silva Jr., Jose Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), 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.

  • 25. Bagloee, S. A.
    et al.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), 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.

  • 26. Balaghi I., M. H.
    et al.
    Antunes, D. J.
    Mamduhi, Mohammad Hossein
    KTH, School of Electrical Engineering and Computer Science (EECS), 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.

  • 27.
    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), 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.

  • 28.
    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.

  • 29.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. Royal Inst Technol, KTH, Stockholm, Sweden..
    Ghauch, Hadi
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    How to Split UL/DL Antennas in Full-Duplex Cellular Networks2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), IEEE, 2018Conference paper (Refereed)
    Abstract [en]

    To further improve the potential of full-duplex communications, networks may employ multiple antennas at the base station or user equipment. To this end, networks that employ current radios usually deal with self-interference and multi-user interference by beamforming techniques. Although previous works investigated beamforming design to improve spectral efficiency, the fundamental question of how to split the antennas at a base station between uplink and downlink in full-duplex networks has not been investigated rigorously. This paper addresses this question by posing antenna splitting as a binary nonlinear optimization problem to minimize the sum mean squared error of the received data symbols. It is shown that this is an NP-hard problem. This combinatorial problem is dealt with by equivalent formulations, iterative convex approximations, and a binary relaxation. The proposed algorithm is guaranteed to converge to a stationary solution of the relaxed problem with much smaller complexity than exhaustive search. Numerical results indicate that the proposed solution is close to the optimal in both high and low self-interference capable scenarios, while the usually assumed antenna splitting is far from optimal. For large number of antennas, a simple antenna splitting is close to the proposed solution. This reveals that the importance of antenna splitting diminishes with the number of antennas.

  • 30.
    Barros da Silva Jr., José Mairton
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems Engineering.
    Sabharwal, Ashutosh
    Rice Univ, Houston, TX USA..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. Ericsson Res, Kista, Sweden..
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems Engineering.
    Low Resolution Phase Shifters Suffice for Full-Duplex mmWave Communications2019In: 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), IEEE , 2019Conference paper (Refereed)
    Abstract [en]

    Full-duplex base-stations with half-duplex nodes, allowing simultaneous uplink and downlink from different nodes, have the potential to double the spectrum efficiency without adding additional complexity at mobile nodes. Hybrid beam forming is commonly used in millimeter wave systems for its implementation efficiency. An important element of hybrid beam-forming is quantized phase shifters. In this paper, we ask if low-resolution phase shifters suffice for beamforming-based full-duplex millimeter wave systems. We formulate the problem of joint design for both self-interference suppression and downlink beamforming as an optimization problem, which we solve using penalty dual decomposition to obtain a near-optimal solution. Numerical results indicate that low-resolution phase shifters can perform close to systems that use infinite phase shifter resolution, and that even a single quantization bit outperforms half-duplex transmissions in both low and high residual self-interference scenarios.

  • 31.
    Baumann, Dominik
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. Max Planck Institute for Intelligent Systems.
    Fast and Resource-Efficient Control of Wireless Cyber-Physical Systems2019Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Cyber-physical systems (CPSs) tightly integrate physical processes with computing and communication to autonomously interact with the surrounding environment.This enables emerging applications such as autonomous driving, coordinated flightof swarms of drones, or smart factories. However, current technology does notprovide the reliability and flexibility to realize those applications. Challenges arisefrom wireless communication between the agents and from the complexity of thesystem dynamics. In this thesis, we take on these challenges and present three maincontributions.We first consider imperfections inherent in wireless networks, such as communication delays and message losses, through a tight co-design. We tame the imperfectionsto the extent possible and address the remaining uncertainties with a suitable controldesign. That way, we can guarantee stability of the overall system and demonstratefeedback control over a wireless multi-hop network at update rates of 20-50 ms.If multiple agents use the same wireless network in a wireless CPS, limitedbandwidth is a particular challenge. In our second contribution, we present aframework that allows agents to predict their future communication needs. Thisallows the network to schedule resources to agents that are in need of communication.In this way, the limited resource communication can be used in an efficient manner.As a third contribution, to increase the flexibility of designs, we introduce machinelearning techniques. We present two different approaches. In the first approach,we enable systems to automatically learn their system dynamics in case the truedynamics diverge from the available model. Thus, we get rid of the assumption ofhaving an accurate system model available for all agents. In the second approach, wepropose a framework to directly learn actuation strategies that respect bandwidthconstraints. Such approaches are completely independent of a system model andstraightforwardly extend to nonlinear settings. Therefore, they are also suitable forapplications with complex system dynamics.

  • 32.
    Baurnann, Dominik
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. Max Planck Institute for Intelligent Systems, Stuttgart/Tübingen, Germany.
    Solowjow, F.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Trimpe, S.
    Event-triggered pulse control with model learning (if Necessary)2019In: Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 792-797, article id 8814333Conference paper (Refereed)
    Abstract [en]

    In networked control systems, communication is a shared and therefore scarce resource. Event-triggered control (ETC) can achieve high performance control with a significantly reduced amount of samples compared to classical, periodic control schemes. However, ETC methods usually rely on the availability of an accurate dynamics model, which is oftentimes not readily available. In this paper, we propose a novel event-triggered pulse control strategy that learns dynamics models if necessary. In addition to adapting to changing dynamics, the method also represents a suitable replacement for the integral part typically used in periodic control.

  • 33. Beerens, R.
    et al.
    Bisoffi, Andrea
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Zaccarian, L.
    Heemels, W. P. M. H.
    Nijmeijer, H.
    Van De Wouw, N.
    Hybrid PID control for transient performance improvement of motion systems with friction2018In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 539-544, article id 8431613Conference paper (Refereed)
    Abstract [en]

    We present a novel reset control approach to improve transient performance of a PID-controlled motion system subject to friction. In particular, a reset integrator is applied to circumvent the depletion and refilling process of a linear integrator when the system overshoots the setpoint, thereby significantly reducing settling times. Moreover, robustness for unknown static friction levels is obtained. A hybrid closed-loop system formulation is derived, and stability follows from a discontinuous Lyapunov-like function and a meagre-limsup invariance argument. The working principle of the controller is illustrated by means of a numerical example.

  • 34.
    Beerens, R.
    et al.
    Eindhoven Univ Technol, Dept Mech Engn, NL-5600 MB Eindhoven, Netherlands..
    Bisoffi, Andrea
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Zaccarian, L.
    Univ Toulouse, LAAS, CNRS, F-31400 Toulouse, France.;Univ Trento, I-38122 Trento, Italy..
    Heemels, W. P. M. H.
    Eindhoven Univ Technol, Dept Mech Engn, NL-5600 MB Eindhoven, Netherlands..
    Nijmeijer, H.
    Eindhoven Univ Technol, Dept Mech Engn, NL-5600 MB Eindhoven, Netherlands..
    van de Wouw, N.
    Eindhoven Univ Technol, Dept Mech Engn, NL-5600 MB Eindhoven, Netherlands.;Univ Minnesota, Civil Environm & Geoengn Dept, Minneapolis, MN 55455 USA..
    Reset integral control for improved settling of PID-based motion systems with friction2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 107, p. 483-492Article in journal (Refereed)
    Abstract [en]

    We present a reset control approach to improve the transient performance of a PID-controlled motion system subject to Coulomb and viscous friction. A reset integrator is applied to circumvent the depletion and refilling process of a linear integrator when the solution overshoots the setpoint, thereby significantly reducing the settling time. Robustness for unknown static friction levels is obtained. The closed-loop system is formulated through a hybrid systems framework, within which stability is proven using a discontinuous Lyapunov-like function and a meagre-limsup invariance argument. The working principle of the proposed reset controller is analyzed in an experimental benchmark study of an industrial high-precision positioning machine.

  • 35.
    Berkane, Soulaimane
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Bisoffi, Andrea
    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 hybrid controller for obstacle avoidance in an n-dimensional euclidean space2019In: 2019 18th European Control Conference, ECC 2019, Institute of Electrical and Electronics Engineers (IEEE), 2019, p. 764-769, article id 8795713Conference paper (Refereed)
    Abstract [en]

    For a vehicle moving in an n-dimensional Euclidean space, we present a construction of a hybrid feedback that guarantees both global asymptotic stabilization of a reference position and avoidance of an obstacle corresponding to a bounded spherical region. The proposed hybrid control algorithm switches between two modes of operation: stabilization (motion-to-goal) and avoidance (boundary-following). The geometric construction of the flow and jump sets of the hybrid controller, exploiting a hysteresis region, guarantees robust switching (chattering-free) between stabilization and avoidance. Simulation results illustrate the performance of the proposed hybrid control approach for a 3-dimensional scenario.

  • 36.
    Berkane, Soulaimane
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Tayebi, A.
    Attitude estimation with intermittent measurements2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 105, p. 415-421Article in journal (Refereed)
    Abstract [en]

    We propose a framework for attitude estimation on the Special Orthogonal group SO(3) using intermittent body-frame vector measurements. We consider the case where the vector measurements are synchronously-intermittent (all measurements are received at the same time) and the case where the vector measurements are asynchronously-intermittent (not all measurements are received at the same time). The proposed observers have a measurement-triggered structure where the attitude is predicted using the continuously measured angular velocity when the vector measurements are not available, and adequately corrected upon the arrival of the vector measurements. A hybrid framework is proposed to capture the behaviour of the closed-loop system by extending the state with timers that are reset at each jump of the observer state. Almost global asymptotic stability is shown using rigorous Lyapunov techniques for hybrid systems.

  • 37.
    Berkane, Soulaimane
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Tayebi, Abdelhamid
    Univ Western Ontario, Dept Elect & Comp Engn, London, ON, Canada.;Lakehead Univ, Dept Elect Engn, Thunder Bay, ON, Canada..
    Teel, Andrew R.
    Univ Calif Santa Barbara, Dept Elect & Comp Engn, Santa Barbara, CA 93106 USA..
    Hybrid Constrained Estimation For Linear Time-Varying Systems2018In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 4643-4648Conference paper (Refereed)
    Abstract [en]

    For linear time-varying systems with possibly constrained states, we propose a hybrid observer that guarantees the containment of the estimated state variables in a prescribed domain of interest. The hybrid observer employs a Kalmantype continuous estimator during the flows while, during the jumps, projects the state estimates onto the set described by the constraint equation. A suitable choice of the flow and jump sets allows to conclude uniform global asymptotic stability of the zero estimation error set.

  • 38.
    Besselink, Bart
    et al.
    Univ Groningen, Jan C Willems Ctr Syst & Control, Groningen, Netherlands.;Univ Groningen, Bernoulli Inst Math Comp Sci & Artificial Intelli, Groningen, Netherlands..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    van der Schaft, Arjan
    Univ Groningen, Jan C Willems Ctr Syst & Control, Groningen, Netherlands.;Univ Groningen, Bernoulli Inst Math Comp Sci & Artificial Intelli, Groningen, Netherlands..
    Contracts as specifications for dynamical systems in driving variable form2019In: 2019 18TH EUROPEAN CONTROL CONFERENCE (ECC), IEEE , 2019, p. 263-268Conference paper (Refereed)
    Abstract [en]

    This paper introduces assume/guarantee contracts on continuous-time control systems, hereby extending contract theories for discrete systems to certain new model classes and specifications. Contracts are regarded as formal characterizations of control specifications, providing an alternative to specifications in terms of dissipativity properties or set-invariance. The framework has the potential to capture a richer class of specifications more suitable for complex engineering systems. The proposed contracts are supported by results that enable the verification of contract implementation and the comparison of contracts. These results are illustrated by an example of a vehicle following system.

  • 39.
    Biel, Martin
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Distributed Stochastic Programming with Applications to Large-Scale Hydropower Operations2019Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Stochastic programming is a subfield of mathematical programming concerned with optimization problems subjected to uncertainty. Many engineering problems with random elements can be accurately modeled as a stochastic program. In particular, decision problems associated with hydropower operations motivate the application of stochastic programming. When complex decision-support problems are considered, the corresponding stochastic programming models often grow too large to store and solve on a single computer. This clarifies the need for parallel approaches that could enable efficient treatment of large-scale stochastic programs in a distributed environment. In this thesis, we develop mathematical and computational tools in order to facilitate distributed stochastic programs that can be efficiently stored and solved.

    First, we present a software framework for stochastic programming implemented in the Julia language. A key feature of the framework is the support for distributing stochastic programs in memory. Moreover, the framework includes a large set of structure-exploiting algorithms for solving stochastic programming problems. These algorithms are based on the classical L-shaped and progressive-hedging algorithms and can run in parallel on distributed stochastic programs. The distributed performance of our software tools is improved by exploring algorithmic innovations and software patterns. We present the architecture of the framework and highlight key implementation details. Finally, we provide illustrative examples of stochastic programming functionality and benchmarks on large-scale problems.

    Then, we pursue further algorithmic improvements to the distributed L-shaped algorithm. Specifically, we consider the use of dynamic cut aggregation. We develop theoretical results on convergence and complexity and then showcase performance improvements in numerical experiments. We suggest several aggregation schemes that are based on parameterized selection rules. Before we perform large-scale experiments, the aggregation parameters are determined by a tuning procedure. In brief, cut aggregation can yield major performance improvements to L-shaped algorithms in distributed settings.

    Finally, we consider an application to hydropower operations. The day-ahead planning problem involves specifying optimal order volumes in a deregulated electricity market, without knowledge of the next-day market price, and then optimizing the hydropower production. We provide a detailed introduction to the day-ahead model and explain how we can implement it with our computational tools. This covers a complete procedure of gathering data, generating forecasts from the data, and finally formulating and solving a stochastic programming model of the day-ahead problem. Using a sample-based algorithm that internally relies on our structure-exploiting solvers, we obtain tight confidence intervals around the optimal solution of the day-ahead problem.

  • 40.
    Biel, Martin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Aytekin, Arda
    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).
    POLO.Jl: Policy-based optimization algorithms in Julia2019In: Advances in Engineering Software, ISSN 0965-9978, E-ISSN 1873-5339, Vol. 136, article id 102695Article in journal (Refereed)
    Abstract [en]

    We present POLO. j1- a Julia package that helps algorithm developers and machine-learning practitioners design and use state-of-the-art parallel optimization algorithms in a flexible and efficient way. POLO. j1 extends our C+ + library POLO, which has been designed and implemented with the same intentions. POLO. j1 not only wraps selected algorithms in POLO and provides an easy mechanism to use data manipulation facilities and loss function definitions in Julia together with the underlying compiled C+ + library, but it also uses the policy-based design technique in a Julian way to help users prototype optimization algorithms from their own building blocks. In our experiments, we observe that there is little overhead when using the compiled C+ + code directly within Julia. We also notice that the performance of algorithms implemented in pure Julia is comparable with that of their C+ + counterparts. Both libraries are hosted on GitHub(1)under the free MIT license, and can be used easily by pulling the pre-built 64-bit architecture Docker images.(2)

  • 41.
    Biel, Martin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Distributed L-shaped Algorithms in Julia2018In: PROCEEDINGS OF PAW-ATM18: 2018 IEEE/ACM PARALLEL APPLICATIONS WORKSHOP, ALTERNATIVES TO MPI (PAW-ATM) / [ed] NDERS JF, 2005, NUMER MATH, V2, P3 okhmal P., 2005, APPLICATIONS OF STOCHASTIC PROGRAMMING, V5, P609 nderoth J, 2003, COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, V24, P207 well Warren B., 2005, APPLICATIONS OF STOCHASTIC PROGRAMMING, V5, P185, IEEE , 2018, p. 57-69Conference paper (Refereed)
    Abstract [en]

    We present LShapedSolvers.jl, a suite of scalable stochastic programming solvers implemented in the Julia programming language. The solvers, which are based on the L-shaped algorithm, run efficiently in parallel, exploit problem structure, and operate on distributed data. The implementation introduces several flexible high-level abstractions that result in a modular design and simplify the development of algorithm variants. In addition, we demonstrate how the abstractions available in the Julia module for distributed computing are exploited to simplify the implementation of the parallel algorithms. The performance of the solvers is evaluated on large-scale problems for finding optimal orders on the Nordic day-ahead electricity market. With 16 worker cores, the fastest algorithm solves a distributed problem with 2.5 million variables and 1.5 million linear constraints about 19 times faster than Gurobi is able to solve the extended form directly.

  • 42.
    Biel, Martin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Norrlof, Mikael
    Efficient Trajectory Reshaping in a Dynamic Environment2018In: 2018 IEEE 15TH INTERNATIONAL WORKSHOP ON ADVANCED MOTION CONTROL (AMC), IEEE, 2018, p. 54-59Conference paper (Refereed)
    Abstract [en]

    A general trajectory planner for optimal control problems is presented and applied to a robot system. The approach is based on timed elastic bands and nonlinear model predictive control. By exploiting the sparsity in the underlying optimization problems the computational effort can be significantly reduced, resulting in a real-time capable planner. In addition, a localization based switching strategy is employed to enforce convergence and stability. The planning procedure is illustrated in a robotics application using a realistic SCARA type robot.

  • 43.
    Bisoffi, Andrea
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    A hybrid barrier certificate approach to satisfy linear temporal logic specifications2018In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 634-639, article id 8430795Conference paper (Refereed)
    Abstract [en]

    In this work we formulate the satisfaction of a (syntactically co-safe) linear temporal logic specification on a physical plant through a recent hybrid dynamical systems formalism. In order to solve this problem, we introduce an extension to such a hybrid system framework of the so-called eventuality property, which matches suitably the condition for the satisfaction of such a temporal logic specification. The eventuality property can be established through barrier certificates, which we derive for the considered hybrid system framework. Using a hybrid barrier certificate, we propose a solution to the original problem. Simulations illustrate the effectiveness of the proposed method. 2018 AACC.

  • 44.
    Björk, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Performance Quantification of Interarea Oscillation Damping Using HVDC2019Licentiate thesis, monograph (Other academic)
    Abstract [en]

    With the transition towards renewable energy, and the deregulation of the electricity market, generation patterns and grid topology are changing. These changes increase the need for transfer capacity. One limiting factor, which sometimes leads to underutilization of the transmission grid, is interarea oscillations. These system-wide modes involve groups of generators oscillating relative to each other and are sometimes hard to control due to their scale and complexity. In this thesis we investigate how high-voltage direct current (HVDC) transmission can be used to attenuate interarea oscillations. The thesis has two main contributions.

    In the first contribution we show how the stability of two asynchronous grids can be improved by modulating the active power of a single interconnecting HVDC link. One concern with modulating HVDC active power is that the interaction between interarea modes of the two grids may have a negative impact on system stability. By studying the controllability Gramian, we show that it is always possible to improve the damping in both grids as long as the frequencies of their interarea modes are not too close. For simplified models, it is explicitly shown how the controllability, and therefore the achievable damping improvements, deteriorates as the frequency difference becomes small.

    The second contribution of the thesis is to show how coordinated control of two (or more) links can be used to avoid interaction between troublesome interarea modes. We investigate the performance of some multivariable control designs. In particular we look at input usage as well as robustness to measurement, communication, and actuator failures. Suitable controllers are thereby characterized.

  • 45.
    Björk, Joakim
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Harnefors, Lennart
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Fundamental Performance Limitations in Utilizing HVDC to Damp Interarea Modes2019In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 34, no 2, p. 1095-1104Article in journal (Refereed)
    Abstract [en]

    This paper considers power oscillation damping (POD) using active power modulation of high-voltage dc transmissions. An analytical study of how the proximity between interarea modal frequencies in two interconnected asynchronous grids puts a fundamental limit to the achievable performance is presented. It is shown that the ratio between the modal frequencies is the sole factor determining the achievable nominal performance. To illustrate the inherent limitations, simulations using a proportional controller tuned to optimize performance in terms of POD are done on a simplified two-machine model. The influence of limited system information and unmodeled dynamics is shown. The analytical result is then further validated on a realistic model with two interconnected 32-bus networks.

  • 46.
    Björk, Joakim
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Harnefors, Lennart
    ABB, Corp Res, Vasteras, Sweden..
    Eriksson, Robert
    Svenska kraftnat, R&D, Sundbyberg, Sweden..
    Analysis of Coordinated HVDC Control for Power Oscillation Damping2018In: Conference Record of the 3rd IEEE International Workshop on Electronic Power Grid, eGrid 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 19-24, article id 8598674Conference paper (Refereed)
    Abstract [en]

    Controlling the active power of high-voltage de (HVDC) transmission that interconnects two asynchronous ac grids can be used to improve the power oscillation damping in both of the interconnected ac systems. Using one HVDC link, achievable performance are limited since control actions may excite modes of similar frequencies in the assisting network. However, with coordinated control of two or more HVDC links, the limitations can be circumvented. With decoupling control the system interactions can be avoided all together. This paper investigates the conditions suitable for decoupling control. It is also shown that decoupling between system modes can be achieved using a proportional controller. The control method is compared to decentralized and H-2 optimal control. The best control method for different system topologies is investigated by looking on input usage and stability following dc link failure.

  • 47. Boem, F.
    et al.
    Zhou, Y.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Parisini, T.
    Distributed Pareto-optimal state estimation using sensor networks2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 93, p. 211-223Article in journal (Refereed)
    Abstract [en]

    A novel model-based dynamic distributed state estimator is proposed using sensor networks. The estimator consists of a filtering step – which uses a weighted combination of information provided by the sensors – and a model-based predictor of the system's state. The filtering weights and the model-based prediction parameters jointly minimize – at each time-step – the bias and the variance of the prediction error in a Pareto optimization framework. The simultaneous distributed design of the filtering weights and of the model-based prediction parameters is considered, differently from what is normally done in the literature. It is assumed that the weights of the filtering step are in general unequal for the different state components, unlike existing consensus-based approaches. The state, the measurements, and the noise components are allowed to be individually correlated, but no probability distribution knowledge is assumed for the noise variables. Each sensor can measure only a subset of the state variables. The convergence properties of the mean and of the variance of the prediction error are demonstrated, and they hold both for the global and the local estimation errors at any network node. Simulation results illustrate the performance of the proposed method, obtaining better results than state of the art distributed estimation approaches.

  • 48. Bombois, X.
    et al.
    Korniienko, A.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Scorletti, G.
    Optimal identification experiment design for the interconnection of locally controlled systems2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 89, p. 169-179Article in journal (Refereed)
    Abstract [en]

    This paper considers the identification of the modules of a network of locally controlled systems (multi-agent systems). Its main contribution is to determine the least perturbing identification experiment that will nevertheless lead to sufficiently accurate models of each module for the global performance of the network to be improved by a redesign of the decentralized controllers. Another contribution is to determine the experimental conditions under which sufficiently informative data (i.e. data leading to a consistent estimate) can be collected for the identification of any module in such a network. 

  • 49.
    Boskos, Dimitris
    et al.
    Univ Calif San Diego, Dept Mech & Aerosp Engn, La Jolla, CA 92093 USA..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    ABSTRACTIONS OF VARYING DECENTRALIZATION DEGREE FOR REACHABILITY OF COUPLED MULTIAGENT SYSTEMS2019In: SIAM Journal of Control and Optimization, ISSN 0363-0129, E-ISSN 1095-7138, Vol. 57, no 5, p. 3471-3495Article in journal (Refereed)
    Abstract [en]

    In this paper we present a decentralized abstraction framework for multiagent systems with couplings in their dynamics, which arise in their popular coordination protocols. The discrete models are basexl on a varying decentralization degree, namely, the agents' individual abstractions are obtained by using discrete information up to a tunable distance in their network graph. Deriving these models at the agent level is essential to address scalability issues which appear in the discretization of systems with a high state dimension. The approach builds on the appropriate discretization of the agents' state space and the selection of a transition time step, which enable the construction of a nonblocking transition system for each agent with quantifiable transition possibilities. The transitions are based on the design of local feedback laws for the manipulation of the coupling terms, which guarantee the execution of the transitions by the continuous systems. For a class of nonlinear agent interconnections, the derivation of such abstractions is always guaranteed, based on sufficient conditions which relate the agents' dynamics and the space/time quantization.

  • 50.
    Boskos, Dimitris
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Decentralized abstractions for multi-agent systems under coupled constraints2019In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 45, p. 1-16Article in journal (Refereed)
    Abstract [en]

    The goal of this paper is to define abstractions for multi-agent systems with feedback interconnection in their dynamics. In the proposed decentralized framework, we specify a finite or countable transition system for each agent which only takes into account the discrete positions of its neighbors. The dynamics of each agent consist of a feedback component which can guarantee certain system and network requirements and induces the coupled constraints, and additional input terms, which can be exploited for high level planning. In this work, we provide sufficient conditions for space and time discretizations which enable the abstraction of the system's behavior through a discrete transition system. Furthermore, these conditions include design parameters whose tuning provides the possibility for multiple transitions, and hence, the construction of transition systems with motion planning capabilities. Published by Elsevier Ltd. All rights reserved.

1234567 1 - 50 of 312
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • 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