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  • 1.
    Colombo, Leonardo
    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.
    Clark, W.
    Bloch, A.
    Time reversal symmetries and zero dynamics for simple hybrid Hamiltonian control systems2018In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 2218-2223Conference paper (Refereed)
    Abstract [en]

    This paper studies Hamel's formalism for simple hybrid mechanical control systems and explores the role of time-reversal symmetries and hybrid zero dynamics to predict the existence of periodic orbits in these control system. A time reversal symmetry in the phase-space permits us to construct a time reversible hybrid Hamiltonian system. If the Hamiltonian function describing the continuous dynamics and the impact map are invariants under a time reversal symmetry on the zero hybrid dynamics, under some mild conditions, we find sufficient conditions for the existence of periodic solutions for the class of simple hybrid Hamiltonian control systems.

  • 2. Dai, L.
    et al.
    Gao, Yulong
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xie, L.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xia, Y.
    Stochastic self-triggered model predictive control for linear systems with probabilistic constraints2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 92, p. 9-17Article in journal (Refereed)
    Abstract [en]

    A stochastic self-triggered model predictive control (SSMPC) algorithm is proposed for linear systems subject to exogenous disturbances and probabilistic constraints. The main idea behind the self-triggered framework is that at each sampling instant, an optimization problem is solved to determine both the next sampling instant and the control inputs to be applied between the two sampling instants. Although the self-triggered implementation achieves communication reduction, the control commands are necessarily applied in open-loop between sampling instants. To guarantee probabilistic constraint satisfaction, necessary and sufficient conditions are derived on the nominal systems by using the information on the distribution of the disturbances explicitly. Moreover, based on a tailored terminal set, a multi-step open-loop MPC optimization problem with infinite prediction horizon is transformed into a tractable quadratic programming problem with guaranteed recursive feasibility. The closed-loop system is shown to be stable. Numerical examples illustrate the efficacy of the proposed scheme in terms of performance, constraint satisfaction, and reduction of both control updates and communications with a conventional time-triggered scheme.

  • 3. Dai, L.
    et al.
    Xia, Y.
    Gao, Yulong
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Cannon, M.
    Distributed stochastic MPC for systems with parameter uncertainty and disturbances2018In: International Journal of Robust and Nonlinear Control, ISSN 1049-8923, E-ISSN 1099-1239, Vol. 28, no 6, p. 2424-2441Article in journal (Refereed)
    Abstract [en]

    A distributed stochastic model predictive control algorithm is proposed for multiple linear subsystems with both parameter uncertainty and stochastic disturbances, which are coupled via probabilistic constraints. To handle the probabilistic constraints, the system dynamics is first decomposed into a nominal part and an uncertain part. The uncertain part is further divided into 2 parts: the first one is constrained to lie in probabilistic tubes that are calculated offline through the use of the probabilistic information on disturbances, whereas the second one is constrained to lie in polytopic tubes whose volumes are optimized online and whose facets' orientations are determined offline. By permitting a single subsystem to optimize at each time step, the probabilistic constraints are then reduced into a set of linear deterministic constraints, and the online optimization problem is transformed into a convex optimization problem that can be performed efficiently. Furthermore, compared to a centralized control scheme, the distributed stochastic model predictive control algorithm only requires message transmissions when a subsystem is optimized, thereby offering greater flexibility in communication. By designing a tailored invariant terminal set for each subsystem, the proposed algorithm can achieve recursive feasibility, which, in turn, ensures closed-loop stability of the entire system. A numerical example is given to illustrate the efficacy of the algorithm. Copyright 

  • 4.
    Demirel, Burak
    et al.
    Paderborn Univ, Chair Automat Control EIME, D-33098 Paderborn, Germany..
    Ghadimi, Euhanna
    Huawei Technol Sweden AB, SE-16494 Kista, Sweden..
    Quevedo, Daniel E.
    Paderborn Univ, Chair Automat Control EIME, D-33098 Paderborn, Germany..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Optimal Control of Linear Systems With Limited Control Actions: Threshold-Based Event-Triggered Control2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 3, p. 1275-1286Article in journal (Refereed)
    Abstract [en]

    We consider a finite-horizon linear-quadratic optimal control problem where only a limited number of control messages are allowed for sending from the controller to the actuator. To restrict the number of control actions computed and transmitted by the controller, we employ a threshold-based event-triggering mechanism that decides whether or not a control message needs to be calculated and delivered. Due to the nature of threshold-based event-triggering algorithms, finding the optimal control sequence requires minimizing a quadratic cost function over a nonconvex domain. In this paper, we first provide an exact solution to this nonconvex problem by solving an exponential number of quadratic programs. To reduce computational complexity, we then propose two efficient heuristic algorithms based on greedy search and the alternating direction method of multipliers technique. Later, we consider a receding horizon control strategy for linear systems controlled by event-triggered controllers, and we further provide a complete stability analysis of receding horizon control that uses finite-horizon optimization in the proposed class. Numerical examples testify to the viability of the presented design technique.

  • 5.
    Everitt, Niklas
    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.
    Galrinho, Miguel
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Open-loop asymptotically efficient model reduction with the Steiglitz–McBride method2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 89, p. 221-234Article in journal (Refereed)
    Abstract [en]

    In system identification, it is often difficult to use a physical intuition when choosing a noise model structure. The importance of this choice is that, for the prediction error method (PEM) to provide asymptotically efficient estimates, the model orders must be chosen according to the true system. However, if only the plant estimates are of interest and the experiment is performed in open loop, the noise model can be over-parameterized without affecting the asymptotic properties of the plant. The limitation is that, as PEM suffers in general from non-convexity, estimating an unnecessarily large number of parameters will increase the risk of getting trapped in local minima. Here, we consider the following alternative approach. First, estimate a high-order ARX model with least squares, providing non-parametric estimates of the plant and noise model. Second, reduce the high-order model to obtain a parametric model of the plant only. We review existing methods to do this, pointing out limitations and connections between them. Then, we propose a method that connects favorable properties from the previously reviewed approaches. We show that the proposed method provides asymptotically efficient estimates of the plant with open-loop data. Finally, we perform a simulation study suggesting that the proposed method is competitive with state-of-the-art methods.

  • 6.
    Feyzmahdavian, Hamid Reza
    et al.
    ABB Corp Res Ctr, S-72226 Vasteras, Sweden..
    Besselink, Bart
    Univ Groningen, Johann Bernoulli Inst Math & Comp Sci, NL-9712 CP Groningen, Netherlands..
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Stability Analysis of Monotone Systems via Max-Separable Lyapunov Functions2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 3, p. 643-656Article in journal (Refereed)
    Abstract [en]

    We analyze stability properties of monotone nonlinear systems via max-separable Lyapunov functions, motivated by the following observations: first, recent results have shown that asymptotic stability of a monotone nonlinear system implies the existence of a max-separable Lyapunov function on a compact set; second, for monotone linear systems, asymptotic stability implies the stronger properties of D-stability and insensitivity to time delays. This paper establishes that for monotone nonlinear systems, equivalence holds between asymptotic stability, the existence of a max-separable Lyapunov function, D-stability, and insensitivity to bounded and unbounded time-varying delays. In particular, a new and general notion of D-stability for monotone nonlinear systems is discussed, and a set of necessary and sufficient conditions for delay-independent stability are derived. Examples show how the results extend the state of the art.

  • 7. Guo, Meng
    et al.
    Bechlioulis, Charalampos P.
    Kyriakopoulos, Kostas J.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Hybrid Control of Multiagent Systems With Contingent Temporal Tasks and Prescribed Formation Constraints2017In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 4, no 4, p. 781-792Article in journal (Refereed)
    Abstract [en]

    In this paper, we present a distributed hybrid control strategy for multiagent systems with contingent temporal tasks and prescribed formation constraints. Each agent is assigned a local task given as a linear temporal logic formula. In addition, two commonly seen kinds of cooperative robotic tasks, namely, service and formation, are requested and exchanged among the agents in real time. The service request is a short-term task provided by one agent to another. On the other hand, the formation request is a relative deployment requirement with predefined transient response imposed by an associated performance function. The proposed hybrid control strategy consists of four major components: 1) the contingent requests handlingmodule; 2) the real-time events monitoring module; 3) the local discrete plan synthesis module; and 4) the continuous control switching module, and it is shown that all local tasks and contingent service/formation requests are fulfilled. Finally, a simulated paradigm demonstrates the proposed control strategy.

  • 8.
    Guo, Meng
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Boskos, Dimitris
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Distributed hybrid control synthesis for multi-agent systems from high-level specifications2018In: Control Subject to Computational and Communication Constraints, Springer Verlag , 2018, 475, p. 241-260Chapter in book (Refereed)
    Abstract [en]

    Current control applications necessitate in many cases the consideration of systems with multiple interconnected components. These components/agents may need to fulfill high-level tasks at a discrete planning layer and also coupled constraints at the continuous control layer. Toward this end, the need for combined decentralized control at the continuous layer and planning at the discrete layer becomes apparent. While there are approaches that handle the problem in a top-down centralized manner, decentralized bottom-up approaches have not been pursued to the same extent. We present here some of our results for the problem of combined, hybrid control and task planning from high-level specifications for multi-agent systems in a bottom-up manner. In the first part, we present some initial results on extending the necessary notion of abstractions to multi-agent systems in a distributed fashion. We then consider a setup where agents are assigned individual tasks in the form of linear temporal logic (LTL) formulas and derive local task planning strategies for each agent. In the last part, the problem of combined distributed task planning and control under coupled continuous constraints is further considered.

  • 9.
    Ha, Huong
    et al.
    Univ Newcastle, Sch Elect Engn & Comp, Newcastle, NSW, Australia..
    Welsh, James S.
    Univ Newcastle, Sch Elect Engn & Comp, Newcastle, NSW, Australia..
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Wahlberg, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    An analysis of the SPARSEVA estimate for the finite sample data case2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 96, p. 141-149Article in journal (Refereed)
    Abstract [en]

    In this paper, we develop an upper bound for the SPARSEVA (SPARSe Estimation based on a VAlidation criterion) estimation error in a general scheme, i.e., when the cost function is strongly convex and the regularized norm is decomposable for a pair of subspaces. We show how this general bound can be applied to a sparse regression problem to obtain an upper bound of the estimation error for the traditional I-1 SPARSEVA problem. Numerical results are used to illustrate the effectiveness of the suggested bound. 

  • 10.
    Larsson, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Golden Angle Modulation2018In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, no 1, p. 98-101Article in journal (Refereed)
    Abstract [en]

    Quadrature amplitude modulation (QAM), with its uniform distribution, exhibits an asymptotic shaping-loss of pi e/6 (approximate to 1.53 dB) with increasing signal-to-noise-ratio compared to the additive white Gaussian noise Shannon capacity. With inspiration gained from special (leaf, flower petal, and seed) packing arrangements (spiral phyllotaxis) found among plants, a novel, shape-versatile, circular symmetric, modulation scheme, the golden angle modulation (GAM) is introduced. Disc-shaped, and complex Gaussian approximating bell-shaped, GAM-signal constellations are considered. For bell-GAM, a high-rate approximation, and a mutual information optimization formulation, are developed. Bell-GAM overcomes the asymptotic shaping-loss seen in QAM, and offers Shannon capacity approaching performance. Transmitter resource limited links, such as space probe-to-earth, and mobile-to-basestation, are cases where GAM could be particularly valuable.

  • 11.
    Li, Nan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Rasmussen, Lars Kildehöj
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Optimized Cooperative Multiple Access in Industrial Cognitive Networks2018In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 14, no 6, p. 2666-2676Article in journal (Refereed)
    Abstract [en]

    We consider optimized cooperation in joint orthogonal multiple access and nonorthogonal multiple access in industrial cognitive networks, in which lots of devices may have to share spectrum and some devices (e.g., those for critical control devices) have higher transmission priority, known as primary users. We consider one secondary transmitter (less important devices) as a potential relay between a primary transmitter and receiver pair. The choice of cooperation scheme differs in terms of use cases. With decode-and-forward relaying, the channel between the primary and secondary users limits the achievable rates especially when it experiences poor channel conditions. To alleviate this problem, we apply analog network coding to directly combine the received primary message for relaying with the secondary message. We find achievable rate regions for these two schemes over Rayleigh fading channels. We then investigate an optimization problem jointly considering orthogonalmultiple access and nonorthogonal multiple access, where the secondary rate is maximized under the constraint of maintaining the primary rate. We find both analytical solutions as well as solutions based on experiments through the time sharing strategy between the primary and secondary system and the transmit power allocation strategy at the secondary transmitter. We show the performance improvements of exploiting analog network coding and the impacts of cooperative schemes and user geometry on achievable rates and resource sharing strategies.

  • 12.
    Liang, Xinyue
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Javid, Alireza M.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, Stockholm, Sweden..
    DISTRIBUTED LARGE NEURAL NETWORK WITH CENTRALIZED EQUIVALENCE2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 2976-2980Conference paper (Refereed)
    Abstract [en]

    In this article, we develop a distributed algorithm for learning a large neural network that is deep and wide. We consider a scenario where the training dataset is not available in a single processing node, but distributed among several nodes. We show that a recently proposed large neural network architecture called progressive learning network (PLN) can be trained in a distributed setup with centralized equivalence. That means we would get the same result if the data be available in a single node. Using a distributed convex optimization method called alternating-direction-method-of-multipliers (ADMM), we perform training of PLN in the distributed setup.

  • 13. Meng, Ziyang
    et al.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Attitude Coordinated Control of Multiple Underactuated Axisymmetric Spacecraft2017In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 4, no 4, p. 816-825Article in journal (Refereed)
    Abstract [en]

    Attitude coordinated control of multiple underactuated spacecraft is studied in this paper. We adopt the parametrization proposed by Tsiotras et al. (1995) to describe attitude kinematics, which has been shown to be very convenient for control of underactuated axisymmetric spacecraft with two control torques. We first propose a partial attitude coordinated controller with angular velocity commands. The controller is based on the exchange of each spacecraft's information with local neighbors and a self-damping term. Under a necessary and general connectivity assumption and by use of a novel Lyapunov function, we show that the symmetry axes of all spacecraft are eventually aligned. Full attitude control of multiple underactuated spacecraft is also considered and a discontinuous distributed control algorithm is proposed. It is shown that the proposed algorithm succeeds in achieving stabilization given that control parameters are chosen properly. Discussions on the cases without self damping are also provided for both partial and full attitude controls. Simulations are given to validate the theoretical results and different steadystate behaviors are observed.

  • 14.
    Molavipour, Sina
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Bassi, German
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Testing for Directed Information Graphs2017In: 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton), IEEE, 2017, p. 212-219Conference paper (Refereed)
    Abstract [en]

    In this paper, we study a hypothesis test to determine the underlying directed graph structure of nodes in a network, where the nodes represent random processes and the direction of the links indicate a causal relationship between said processes. Specifically, a k-th order Markov structure is considered for them, and the chosen metric to determine a connection between nodes is the directed information. The hypothesis test is based on the empirically calculated transition probabilities which are used to estimate the directed information. For a single edge, it is proven that the detection probability can be chosen arbitrarily close to one, while the false alarm probability remains negligible. When the test is performed on the whole graph, we derive bounds for the false alarm and detection probabilities, which show that the test is asymptotically optimal by properly setting the threshold test and using a large number of samples. Furthermore, we study how the convergence of the measures relies on the existence of links in the true graph.

  • 15.
    Molin, Adam
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Ramesh, C.
    Esen, H.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Innovations-based priority assignment for control over CAN-like networks2015In: 54th IEEE Conference on Decision and Control (CDC), IEEE conference proceedings, 2015, p. 4163-4169Conference paper (Refereed)
    Abstract [en]

    We present an innovations-based prioritization mechanism to efficiently use network resources for data gathering, without compromising the real-time decision making capability of the control systems. In the envisioned protocol, each sensor assigns the Value of Information (VoI) contained in its current observations for the network as the priority. Tournaments are used to compare priorities and assign transmission slots, like in the CAN bus protocol. By using a rollout strategy, we derive feasible algorithms for computing the VoI-based priorities for the case of coupled and decoupled systems. In the case of decoupled systems, performance guarantees with regard to the control cost of the VoI-based strategy are identified. We illustrate the efficiency of the proposed approach on a platooning example in which the vehicles receive measurements from multiple sensors.

  • 16.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Boskos, Dimitris
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    On the timed temporal logic planning of coupled multi-agent systems2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 97, p. 339-345Article in journal (Refereed)
    Abstract [en]

    This paper presents a fully automated procedure for controller synthesis for multi-agent systems under coupling constraints. Each agent is modeled with dynamics consisting of two terms: the first one models the coupling constraints and the other one is an additional bounded control input. We aim to design these inputs so that each agent meets an individual high-level specification given as a Metric Interval Temporal Logic (MITL). First, a decentralized abstraction that provides a space and time discretization of the multi-agent system is designed. Second, by utilizing this abstraction and techniques from formal verification, we propose an algorithm that computes the individual runs which provably satisfy the high-level tasks. The overall approach is demonstrated in a simulation example conducted in MATLAB environment. 

  • 17.
    Park, Pangun
    et al.
    Chungnam Natl Univ, Dept Radio & Informat Commun Engn, Daejeon 305764, South Korea..
    Ergen, Sinem Coleri
    Koc Univ, Dept Elect & Elect Engn, TR-34450 Istanbul, Turkey..
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Lu, Chenyang
    Washington Univ, Dept Comp Sci & Engn, St Louis, MO 63130 USA..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Wireless Network Design for Control Systems: A Survey2018In: IEEE Communications Surveys and Tutorials, ISSN 1553-877X, E-ISSN 1553-877X, Vol. 20, no 2, p. 978-1013Article in journal (Refereed)
    Abstract [en]

    Wireless networked control systems (WNCSs) are composed of spatially distributed sensors, actuators, and controllers communicating through wireless networks instead of conventional point-to-point wired connections. Due to their main benefits in the reduction of deployment and maintenance costs, large flexibility and possible enhancement of safety, WNCS are becoming a fundamental infrastructure technology for critical control systems in automotive electrical systems, avionics control systems, building management systems, and industrial automation systems. The main challenge in WNCS is to jointly design the communication and control systems considering their tight interaction to improve the control performance and the network lifetime. In this survey, we make an exhaustive review of the literature on wireless network design and optimization for WNCS. First, we discuss what we call the critical interactive variables including sampling period, message delay, message dropout, and network energy consumption. The mutual effects of these communication and control variables motivate their joint tuning. We discuss the analysis and design of control systems taking into account the effect of the interactive variables on the control system performance. Moreover, we discuss the effect of controllable wireless network parameters at all layers of the communication protocols on the probability distribution of these interactive variables. We also review the current wireless network standardization for WNCS and their corresponding methodology for adapting the network parameters. Finally, we present the state-of-the-art wireless network design and optimization for WNCS, while highlighting the tradeoff between the achievable performance and complexity of various approaches. We conclude the survey by highlighting major research issues and identifying future research directions.

  • 18. Ren, Xiaoqiang
    et al.
    Wu, Junfeng
    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 Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Shi, Guodong
    Shi, Ling
    Infinite Horizon Optimal Transmission Power Control for Remote State Estimation Over Fading Channels2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 1, p. 85-100Article in journal (Refereed)
    Abstract [en]

    This paper studies the joint design over an infinite horizon of the transmission power controller and remote estimator for state estimation over fading channels. A sensor observes a dynamic process and sends its observations to a remote estimator over a wireless fading channel characterized by a time-homogeneous Markov chain. The successful transmission probability depends on both the channel gains and the transmission power used by the sensor. The transmission power control rule and the remote estimator should be jointly designed, aiming to minimize an infinite-horizon cost consisting of the power usage and the remote estimation error. We formulate the joint optimization problem as an average cost belief-state Markov decision process and prove that there exists an optimal deterministic and stationary policy. We then show that when the monitored dynamic process is scalar or the system matrix is orthogonal, the optimal remote estimates depend only on the most recently received sensor observation, and the optimal transmission power is symmetric and monotonically increasing with respect to the norm of the innovation error.

  • 19.
    Sandberg, Henrik
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Dan, György
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Thobaben, Ragnar
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Differentially private state estimation in distribution networks with smart meters2015In: Proceedings of the IEEE Conference on Decision and Control, IEEE conference proceedings, 2015, p. 4492-4498Conference paper (Refereed)
    Abstract [en]

    State estimation is routinely being performed in high-voltage power transmission grids in order to assist in operation and to detect faulty equipment. In low- and medium-voltage power distribution grids, on the other hand, few real-time measurements are traditionally available, and operation is often conducted based on predicted and historical data. Today, in many parts of the world, smart meters have been deployed at many customers, and their measurements could in principle be shared with the operators in real time to enable improved state estimation. However, customers may feel reluctance in doing so due to privacy concerns. We therefore propose state estimation schemes for a distribution grid model, which ensure differential privacy to the customers. In particular, the state estimation schemes optimize different performance criteria, and a trade-off between a lower bound on the estimation performance versus the customers' differential privacy is derived. The proposed framework is general enough to be applicable also to other distribution networks, such as water networks.

  • 20.
    Schillinger, Philipp
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. Bosch Ctr Artificial Intelligence, Robert Bosch Campus 1, DE-71272 Renningen, Germany.
    Buerger, Mathias
    Bosch Ctr Artificial Intelligence, Robert Bosch Campus 1, DE-71272 Renningen, Germany..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Simultaneous task allocation and planning for temporal logic goals in heterogeneous multi-robot systems2018In: The international journal of robotics research, ISSN 0278-3649, E-ISSN 1741-3176, Vol. 37, no 7, p. 818-838Article in journal (Refereed)
    Abstract [en]

    This paper describes a framework for automatically generating optimal action-level behavior for a team of robots based on temporal logic mission specifications under resource constraints. The proposed approach optimally allocates separable tasks to available robots, without requiring a priori an explicit representation of the tasks or the computation of all task execution costs. Instead, we propose an approach for identifying sub-tasks in an automaton representation of the mission specification and for simultaneously allocating the tasks and planning their execution. The proposed framework avoids the need to compute a combinatorial number of possible assignment costs, where each computation itself requires solving a complex planning problem. This can improve computational efficiency compared with classical assignment solutions, in particular for on-demand missions where task costs are unknown in advance. We demonstrate the applicability of the approach with multiple robots in an existing office environment and evaluate its performance in several case study scenarios.

  • 21. Stanković, M. S.
    et al.
    Stanković, S. S.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Distributed time synchronization for networks with random delays and measurement noise2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 93, p. 126-137Article in journal (Refereed)
    Abstract [en]

    In this paper a new distributed asynchronous algorithm is proposed for time synchronization in networks with random communication delays, measurement noise and communication dropouts. Three different types of the drift correction algorithm are introduced, based on different kinds of local time increments. Under nonrestrictive conditions concerning network properties, it is proved that all the algorithm types provide convergence in the mean square sense and with probability one (w.p.1) of the corrected drifts of all the nodes to the same value (consensus). An estimate of the convergence rate of these algorithms is derived. For offset correction, a new algorithm is proposed containing a compensation parameter coping with the influence of random delays and special terms taking care of the influence of both linearly increasing time and drift correction. It is proved that the corrected offsets of all the nodes converge in the mean square sense and w.p.1. An efficient offset correction algorithm based on consensus on local compensation parameters is also proposed. It is shown that the overall time synchronization algorithm can also be implemented as a flooding algorithm with one reference node. It is proved that it is possible to achieve bounded error between local corrected clocks in the mean square sense and w.p.1. Simulation results provide an additional practical insight into the algorithm properties and show its advantage over the existing methods.

  • 22.
    Sun, Peng
    et al.
    Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China..
    Wu, Liantao
    Shanghai Huawei Technol Corp Campus, Shanghai 200040, Peoples R China..
    Wang, Zhibo
    Wuhan Univ, Sch Cyber Sci & Engn, Wuhan 430072, Hubei, Peoples R China.;Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210023, Jiangsu, Peoples R China..
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Wang, Zhi
    Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China..
    Sparsest Random Sampling for Cluster-Based Compressive Data Gathering in Wireless Sensor Networks2018In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 36383-36394Article in journal (Refereed)
    Abstract [en]

    Compressive data gathering (CDG) has been recognized as a promising technique to collect sensory data in wireless sensor networks (WSNs) with reduced energy cost and better traffic load balancing. Besides, clustering is often integrated into CDG to further facilitate the network performance. However, existing cluster-based CDG methods generally require a large number of sensor nodes to participate in each compressive sensing (CS) measurement gathering and rarely consider possible node failures due to power depletion or malicious attacks, leading to insufficient energy efficiency and poor system robustness. In this paper, we propose a sparsest random sampling scheme for cluster-based CDG (SRS-CCDG) in WSNs to achieve energy efficient and robust data collection. Specifically, sensor nodes are organized into clusters. In each round of data gathering, a random subset of sensor nodes sense the monitored field and transmit their measurements to the corresponding cluster heads (CHs). Then, each CH transmits the data gathered within its cluster to the sink. In SRS-CCDG, each sensor reading is regarded as one CS measurement, and both intra-cluster and inter-cluster data transmissions can be realized by two methods, i.e., relaying or direct transmission. Furthermore, we propose analytical models that study the relationship between the size of clusters and the energy cost when using different intra-cluster and inter-cluster transmission schemes, aimed at finding the optimal size of clusters and transmission schemes that could lead to minimum energy cost. Then, we present a centralized clustering algorithm based on the theoretical analysis. Finally, we investigate the robustness of signal recovery performance of SRS-CCDG when node failures happen. Extensive simulations demonstrate that SRS-CCDG can significantly reduce the energy cost and improve the system robustness to node failures.

  • 23.
    Sundin, Martin
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Venkitaraman, Arun
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Jansson, Magnus
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    A Connectedness Constraint for Learning Sparse Graphs2017In: 2017 25TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), IEEE , 2017, p. 151-155Conference paper (Refereed)
    Abstract [en]

    Graphs are naturally sparse objects that are used to study many problems involving networks, for example, distributed learning and graph signal processing. In some cases, the graph is not given, but must be learned from the problem and available data. Often it is desirable to learn sparse graphs. However, making a graph highly sparse can split the graph into several disconnected components, leading to several separate networks. The main difficulty is that connectedness is often treated as a combinatorial property, making it hard to enforce in e.g. convex optimization problems. In this article, we show how connectedness of undirected graphs can be formulated as an analytical property and can be enforced as a convex constraint. We especially show how the constraint relates to the distributed consensus problem and graph Laplacian learning. Using simulated and real data, we perform experiments to learn sparse and connected graphs from data.

  • 24.
    Talebi Mazraeh Shahi, Mohammad Sadegh
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Zou, Zhenhua
    Ericsson Res, SE-16483 Stockholm, Sweden..
    Combes, Richard
    Cent Supelec L2S, Telecommun Dept, F-91192 Gif Sur Yvette, France..
    Proutiere, Alexandre
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Johansson, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Stochastic Online Shortest Path Routing: The Value of Feedback2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 4, p. 915-930Article in journal (Refereed)
    Abstract [en]

    This paper studies online shortest path routing over multihop networks. Link costs or delays are time varying and modeled by independent and identically distributed random processes, whose parameters are initially unknown. The parameters, and hence the optimal path, can only be estimated by routing packets through the network and observing the realized delays. Our aim is to find a routing policy that minimizes the regret (the cumulative difference of expected delay) between the path chosen by the policy and the unknown optimal path. We formulate the problem as a combinatorial bandit optimization problem and consider several scenarios that differ in where routing decisions are made and in the information available when making the decisions. For each scenario, we derive a tight asymptotic lower bound on the regret that has to be satisfied by any online routing policy. Three algorithms, with a tradeoff between computational complexity and performance, are proposed. The regret upper bounds of these algorithms improve over those of the existing algorithms. We also assess numerically the performance of the proposed algorithms and compare it to that of existing algorithms.

  • 25.
    Uddin, Misbah
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Stadler, Rolf
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Clemm, Alexander
    Huawei USA Futurewei Technol Inc, Santa Clara, CA USA..
    A bottom-up design for spatial search in large networks and clouds2018In: International Journal of Network Management, ISSN 1055-7148, E-ISSN 1099-1190, Vol. 28, no 6, article id e2041Article in journal (Refereed)
    Abstract [en]

    APPENDIX Information in networked systems often has spatial semantics: routers, sensors, or virtual machines have coordinates in a geographical or virtual space, for instance. In this paper, we propose a design for a spatial search system that processes queries against spatial information that is maintained in local databases inside a large networked system. In contrast to previous works in spatial databases and peer-to-peer designs, our design is bottom-up, which makes query routing network aware and thus efficient, and which facilitates system bootstrapping and adaptation. Key to our design is a protocol that creates and maintains a distributed index of object locations based on information from local databases and the underlying network topology. The index builds upon minimum bounding rectangles to efficiently encode locations. We present a generic search protocol that is based on an echo protocol and uses the index to prune the search space and perform query routing. The response times of search queries increase with the diameter of the network, which is asymptotically optimal. We study the performance of the protocol through simulation in static and dynamic network environments, for different network topologies, and for network sizes up to 100 000 nodes. In most experiments, the overhead incurred by our protocol lies well below 30% of a hypothetical optimal protocol. In addition, the protocol provides high accuracy under significant churn.

  • 26.
    Valenzuela, Patricio E.
    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. KTH Royal Inst Technol, Sch Elect Engn, Dept Automat Control, SE-10044 Stockholm, Sweden. KTH Royal Inst Technol, Sch Elect Engn, ACCESS Linnaeus Ctr, SE-10044 Stockholm, Sweden..
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Analysis of averages over distributions of Markov processes2018In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 98, p. 354-357Article in journal (Refereed)
    Abstract [en]

    In problems of optimal control of Markov decision processes and optimal design of experiments, the occupation measure of a Markov process is designed in order to maximize a specific reward function. When the memory of such a process is too long, or the process is non-Markovian but mixing, it makes sense to approximate it by that of a shorter memory Markov process. This note provides a specific bound for the approximation error introduced in these schemes. The derived bound is then applied to the proposed solution of a recently introduced approach to optimal input design for nonlinear systems.

  • 27.
    Valerio, Turri
    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.
    Flärdh, O.
    Mårtensson, Jonas
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. 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), Automatic Control.
    Fuel-optimal look-ahead adaptive cruise control for heavy-duty vehicles2018In: 2018 Annual American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1841-1848, article id 8431494Conference paper (Refereed)
    Abstract [en]

    In this paper, we investigate the problem of how to optimally control a heavy-duty vehicle following another one, commonly referred as ad-hoc or non-cooperative platooning. The problem is formulated as an optimal control problem that exploits road topography information and the knowledge of the preceding vehicle speed trajectory to compute the optimal engine torque and gear request for the vehicle under control. The optimal control problem is implemented by dynamic programming and is tested in a simulation study that compares the performance of multiple longitudinal control strategies. The proposed look-ahead adaptive cruise controller is able to achieve fuel saving up to 7% with respect to the use of a reference vehicle-following controller, by combining the benefits of adjusting the inter-vehicular distance according to the future slope with those of alternating phases of throttling and freewheeling (driving in neutral gear).

  • 28.
    van de Hoef, Sebastian
    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.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    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.
    Fuel-Efficient En Route Formation of Truck Platoons2018In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 19, no 1, p. 102-112Article in journal (Refereed)
    Abstract [en]

    The problem of how to coordinate a large fleet of trucks with a given itinerary to enable fuel-efficient platooning is considered. Platooning is a promising technology that enables trucks to save significant amounts of fuel by driving close together and thus reducing air drag. A setting is considered in which each truck in a fleet is provided with a start location, a destination, a departure time, and an arrival deadline from a higher planning level. Fuel-efficient plans should be computed. The plans consist of routes and speed profiles that allow trucks to arrive by their arrival deadlines. Hereby, trucks can meet on common parts of their routes and form platoons, resulting in decreased fuel consumption. We formulate a combinatorial optimization problem that combines plans involving only two vehicles. We show that this problem is difficult to solve for large problem instances. Hence, a heuristic algorithm is proposed. The resulting plans are further optimized using convex optimization techniques. The method is evaluated with Monte Carlo simulations in a realistic setting. We demonstrate that the proposed algorithm can compute plans for thousands of trucks and that significant fuel savings can be achieved.

  • 29.
    Venkitaraman, Arun
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, SE-10044 Stockholm, Sweden..
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, SE-10044 Stockholm, Sweden..
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH Royal Inst Technol, Sch Elect Engn, Dept Informat Sci & Engn, SE-10044 Stockholm, Sweden..
    MULTI-KERNEL REGRESSION FOR GRAPH SIGNAL PROCESSING2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 4644-4648Conference paper (Refereed)
    Abstract [en]

    We develop a multi-kernel based regression method for graph signal processing where the target signal is assumed to be smooth over a graph. In multi-kernel regression, an effective kernel function is expressed as a linear combination of many basis kernel functions. We estimate the linear weights to learn the effective kernel function by appropriate regularization based on graph smoothness. We show that the resulting optimization problem is shown to be convex and propose an accelerated projected gradient descent based solution. Simulation results using real-world graph signals show efficiency of the multi-kernel based approach over a standard kernel based approach.

  • 30.
    Wahlström, Johan
    et al.
    Univ Oxford, Dept Comp Sci, Oxford OX1 2JD, England..
    Skog, Isaac
    Linköping Univ, Dept Elect Engn, S-58183 Linköping, Sweden.
    Nordström, Robin Larsson
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Fusion of OBD and GNSS Measurements of Speed2018In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 67, no 7, p. 1659-1667Article in journal (Refereed)
    Abstract [en]

    There are two primary sources of sensor measurements for driver behavior profiling within insurance telematics and fleet management. The first is the on-board diagnostics system, typically found within most modern cars. The second is the global navigation satellite system, whose associated receivers commonly are embedded into smartphones or off-the-shelf telematics devices. In this paper, we present maximum likelihood and maximum a posteriori estimators for the problem of fusing speed measurements from these two sources to jointly estimate a vehicle's speed and the scale factor of the wheel speed sensors. In addition, we analyze the performance of the estimators by use of the Cramer-Rao bound, and discuss the estimation of model parameters describing measurement errors and vehicle dynamics. Last, simulations and real-world data are used to show that the proposed estimators yield a substantial performance gain compared to when employing only one of the two measurement sources.

  • 31.
    Wu, Junfeng
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Shi, Guodong
    Australian Natl Univ, Res Sch Engn, Canberra, ACT 0200, Australia..
    Anderson, Brian D. O.
    Australian Natl Univ, Res Sch Engn, Canberra, ACT 0200, Australia..
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Kalman Filtering Over Gilbert-Elliott Channels: Stability Conditions and Critical Curve2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 4, p. 1003-1017Article in journal (Refereed)
    Abstract [en]

    This paper investigates the stability of Kalman filtering over Gilbert-Elliott channels where random packet drops follow a time-homogeneous two-state Markov chain whose state transition is determined by a pair of failure and recovery rates. First of all, we establish a relaxed condition guaranteeing peak-covariance stability described by an inequality in terms of the spectral radius of the system matrix and transition probabilities of the Markov chain. We further show that the condition can be interpreted using a linear matrix inequality feasibility problem. Next, we prove that the peak-covariance stability implies mean-square stability, if the system matrix has no defective eigenvalues on the unit circle. This connection between the two stability notions holds for any random packet drop process. We prove that there exists a critical curve in the failure-recovery rate plane, below which the Kalman filter is mean-square stable and no longer mean-square stable above. Finally, a lower bound for this critical failure rate is obtained making use of the relationship we establish between the two stability criteria, based on an approximate relaxation of the system matrix.

  • 32.
    Yanggratoke, Rerngvit
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Ahmed, Jawwad
    Ardelius, John
    Flinta, Christofer
    Johnsson, Andreas
    Gillblad, Daniel
    Stadler, Rolf
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. Swedish Institute of Computer Science (SICS), Sweden.
    A service-agnostic method for predicting service metrics in real time2018In: International Journal of Network Management, ISSN 1055-7148, E-ISSN 1099-1190, Vol. 28, no 2, article id e1991Article in journal (Refereed)
    Abstract [en]

    We predict performance metrics of cloud services using statistical learning, whereby the behaviour of a system is learned from observations. Specifically, we collect device and network statistics from a cloud testbed and apply regression methods to predict, in real-time, client-side service metrics for video streaming and key-value store services. Results from intensive evaluation on our testbed indicate that our method accurately predicts service metrics in real time (mean absolute error below 16% for video frame rate and read latency, for instance). Further, our method is service agnostic in the sense that it takes as input operating systems and network statistics instead of service-specific metrics. We show that feature set reduction significantly improves the prediction accuracy in our case, while simultaneously reducing model computation time. We find that the prediction accuracy decreases when, instead of a single service, both services run on the same testbed simultaneously or when the network quality on the path between the server cluster and the client deteriorates. Finally, we discuss the design and implementation of a real-time analytics engine, which processes streams of device statistics and service metrics from testbed sensors and produces model predictions through online learning.

  • 33.
    Yoo, Jaehyun
    et al.
    KTH, School of Electrical Engineering (EES). KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Molin, Adam
    Jafarian, Matin
    KTH, School of Education and Communication in Engineering Science (ECE). KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Esen, Hasan
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Event-triggered Model Predictive Control with Machine Learning for Compensation of Model Uncertainties2017In: 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 5463-5468Conference paper (Refereed)
    Abstract [en]

    As one of the extensions of model predictive control (MPC), event-triggered MPC takes advantage of the reduction of control updates. However, approaches to event-triggered MPCs may be subject to frequent event-triggering instants in the presence of large disturbances. Motivated by this, this paper suggests an application of machine learning to this control method in order to learn a compensation model for disturbance attenuation. The suggested method improves both event-triggering policy efficiency and control accuracy compared to previous approaches to event-triggered MPCs. We employ the radial basis function (RBF) kernel based machine learning technique. By the universial approximation property of the RBF, which imposes an upper bound on the training error, we can present the stability analysis of the learningaided control system. The proposed algorithm is evaluated by means of position control of a nonholonomic robot subject to state-dependent disturbances. Simulation results show that the developed method yields not only two times less event triggering instants, but also improved tracking performance.

  • 34.
    Zaki, Ahmed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Venkitaraman, Arun
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rasmussen, Lars Kildehoj
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Greedy Sparse Learning Over Network2018In: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, ISSN 2373-776X, Vol. 4, no 3, p. 424-435Article in journal (Refereed)
    Abstract [en]

    In this paper, we develop a greedy algorithm for solving the problem of sparse learning over a right stochastic network in a distributed manner. The nodes iteratively estimate the sparse signal by exchanging a weighted version of their individual intermediate estimates over the network. We provide a restricted-isometry-property (RIP)-based theoretical performance guarantee in the presence of additive noise. In the absence of noise, we show that under certain conditions on the RIP-constant of measurement matrix at each node of the network, the individual node estimates collectively converge to the true sparse signal. Furthermore, we provide an upper bound on the number of iterations required by the greedy algorithm to converge. Through simulations, we also show that the practical performance of the proposed algorithm is better than other state-of-the-art distributed greedy algorithms found in the literature.

  • 35.
    Zaki, Ahmed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Venkitaraman, Arun
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rasmussen, Lars Kildehöj
    Distributed Greedy Sparse Learning over Doubly Stochastic Networks2017In: 2017 25TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), IEEE , 2017, p. 361-364Conference paper (Refereed)
    Abstract [en]

    In this paper, we develop a greedy algorithm for sparse learning over a doubly stochastic network. In the proposed algorithm, nodes of the network perform sparse learning by exchanging their individual intermediate variables. The algorithm is iterative in nature. We provide a restricted isometry property (RIP)-based theoretical guarantee both on the performance of the algorithm and the number of iterations required for convergence. Using simulations, we show that the proposed algorithm provides good performance.

  • 36.
    Zhang, Heng
    et al.
    Huaihai Inst Technol, Lianyungang, Peoples R China..
    Qi, Yifei
    Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou, Zhejiang, Peoples R China..
    Wu, Junfeng
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Fu, Lingkun
    Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou, Zhejiang, Peoples R China..
    He, Lidong
    Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou, Zhejiang, Peoples R China..
    DoS Attack Energy Management Against Remote State Estimation2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 1, p. 383-394Article in journal (Refereed)
    Abstract [en]

    This paper considers a remote state estimation problem, where a sensor measures the state of a linear discrete-time process and has computational capability to implement a local Kalman filter based on its own measurements. The sensor sends its local estimates to a remote estimator over a communication channel that is exposed to a Denial-of-Service (DoS) attacker. The DoS attacker, subject to limited energy budget, intentionally jams the communication channel by emitting interference noises with the purpose of deteriorating estimation performance. In order to maximize attack effect, following the existing answer to "when to attack the communication channel", in this paper we manage to solve the problem of "how much power the attacker should use to jam the channel in each time". For the static attack energy allocation problem, when the system matrix is normal, we derive a sufficient condition for when the maximum number of jamming operations should be used. The associated jamming power is explicitly provided. For a general system case, we propose an attack power allocation algorithm and show the computational complexity of the proposed algorithm is not worse than O(T), where T is the length of the time horizon considered. When the attack can receive the real-time ACK information, we formulate a dynamic attack energy allocation problem, and transform it to a Markov Decision Process to find the optimal solution.

  • 37.
    Zhang, Kuize
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Giva, Alessandro
    Weak (approximate) detectability of labeled Petri net systems with inhibitor arcs2018In: IFAC PAPERSONLINE, ISSN 2405-8963, Vol. 51, no 7, p. 167-171Article in journal (Refereed)
    Abstract [en]

    Weak (approximate) detectability of a labeled Petri net (LPN) system (with inhibitor arcs) is a property such that if the property is satisfied then there exists an infinite label sequence generated by the system such that all markings after a time step can determined (in a prescribed subset of reachable markings) by the label sequence. Specifically, we prove that the problems of deciding weak detectability of LPN systems with inhibitor arcs and weak approximate detectability of LPN systems are both undecidable.

  • 38.
    Zhao, Shiyu
    et al.
    Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S10 2TN, S Yorkshire, England..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Sun, Zhiyong
    Australian Natl Univ, Res Sch Engn, Canberra, ACT 0200, Australia..
    Bauso, Dario
    Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S10 2TN, S Yorkshire, England..
    A General Approach to Coordination Control of Mobile Agents With Motion Constraints2018In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, no 5, p. 1509-1516Article in journal (Refereed)
    Abstract [en]

    This paper proposes a general approach to design convergent coordination control laws for multiagent systems subject to motion constraints. The main contribution of this paper is to prove in a constructive way that a gradient-descent coordination control law designed for single integrators can be easily modified to adapt for various motion constraints such as nonholonomic dynamics, linear/angular velocity saturation, and other path constraints while preserving the convergence of the entire multiagent system. The proposed approach is applicable to a wide range of coordination tasks such as rendezvous and formation control in two and three dimensions. As a special application, the proposed approach solves the problem of distance-based formation control subject to nonholonomic and velocity saturation constraints.

  • 39.
    Zhu, Shanying
    et al.
    Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China.;Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China..
    Chen, Cailian
    Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China.;Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China..
    Xu, Jinming
    Arizona State Univ, Ira A Fulton Sch Engn, Tempe, AZ 85281 USA..
    Guan, Xinping
    Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China.;Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China..
    Xie, Lihua
    Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Mitigating Quantization Effects on Distributed Sensor Fusion: A Least Squares Approach2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 13, p. 3459-3474Article in journal (Refereed)
    Abstract [en]

    In this paper, we consider the problem of sensor fusion over networks with asymmetric links, where the common goal is linear parameter estimation. For the scenario of bandwidth-constrained networks, existing literature shows that nonvanishing errors always occur, which depend on the quantization scheme. To tackle this challenging issue, we introduce the notion of virtual measurements and propose a distributed solution LS-DSFS, which is a combination of a quantized consensus algorithm and the least squares approach. We provide detailed analysis of the LS-DSFS on its performance in terms of unbiasedness and mean square property. Analytical results show that the LS-DSFS is effective in smearing out the quantization errors, and achieving the minimum mean square error (MSE) among the existing centralized and distributed algorithms. Moreover, we characterize its rate of convergence in the mean square sense and that of the mean sequence. More importantly, we find that the LS-DSFS outperforms the centralized approaches within a moderate number of iterations in terms of MSE, and will always consume less energy and achieve more balanced energy expenditure as the number of nodes in the network grows. Simulation results are presented to validate theoretical findings and highlight the improvements over existing algorithms.

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