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  • 1.
    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.

  • 2. Ahmed, J.
    et al.
    Josefsson, T.
    Johnsson, A.
    Flinta, C.
    Moradi, F.
    Pasquini, R.
    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.
    Automated diagnostic of virtualized service performance degradation2018In: IEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 1-9Conference paper (Refereed)
    Abstract [en]

    Service assurance for cloud applications is a challenging task and is an active area of research for academia and industry. One promising approach is to utilize machine learning for service quality prediction and fault detection so that suitable mitigation actions can be executed. In our previous work, we have shown how to predict service-level metrics in real-time just from operational data gathered at the server side. This gives the service provider early indications on whether the platform can support the current load demand. This paper provides the logical next step where we extend our work by proposing an automated detection and diagnostic capability for the performance faults manifesting themselves in cloud and datacenter environments. This is a crucial task to maintain the smooth operation of running services and minimizing downtime. We demonstrate the effectiveness of our approach which exploits the interpretative capabilities of Self- Organizing Maps (SOMs) to automatically detect and localize different performance faults for cloud services. © 2018 IEEE.

  • 3.
    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.

  • 4.
    Colombo, Leonardo
    et al.
    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.
    Optimal Control of Left-Invariant Multi-Agent Systems with Asymmetric Formation Constraints2018In: 2018 European Control Conference, ECC 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1728-1733, article id 8550238Conference paper (Refereed)
    Abstract [en]

    In this work we study an optimal control problem for a multi-agent system modeled by an undirected formation graph with nodes describing the kinematics of each agent, given by a left invariant control system on a Lie group. The agents should avoid collision between them in the workspace. Such a task is done by introducing some potential functions into the cost functional for the optimal control problem, corresponding to fictitious forces, induced by the formation constraint among agents, that break the symmetry of the individual agents and the cost functions, and rendering the optimal control problem partially invariant by a Lie group of symmetries. Reduced necessary conditions for the existence of normal extremals are obtained using techniques of variational calculus on manifolds. As an application we study an optimal control problem for multiple unicycles.

  • 5. 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.

  • 6. 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 

  • 7.
    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.

  • 8.
    Du, Wen
    et al.
    Univ North Texas, Dept Elect Engn, Denton, TX 76203 USA..
    Yi, Xinlei
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    George, Jemin
    US Army Res Lab, Adelphi, MD 20783 USA..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Yang, Tao
    Univ North Texas, Dept Elect Engn, Denton, TX 76203 USA..
    Distributed Optimization with Dynamic Event-Triggered Mechanisms2018In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 969-974Conference paper (Refereed)
    Abstract [en]

    In this paper, we consider the distributed optimization problem, whose objective is to minimize the global objective function, which is the sum of local convex objective functions, by using local information exchange. To avoid continuous communication among the agents, we propose a distributed algorithm with a dynamic event-triggered communication mechanism. We show that the distributed algorithm with the dynamic event-triggered communication scheme converges to the global minimizer exponentially, if the underlying communication graph is undirected and connected. Moreover, we show that the event-triggered algorithm is free of Zeno behavior. For a particular case, we also explicitly characterize the lower bound for inter-event times. The theoretical results are illustrated by numerical simulations.

  • 9.
    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.

  • 10.
    Ferizbegovic, Mina
    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.
    Weighted Null-Space Fitting for Cascade Networks with Arbitrary Location of Sensors and Excitation Signals2018In: : 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 4707-4712Conference paper (Refereed)
    Abstract [en]

    Identification of a complete dynamic network affected by sensor noise using the prediction error method is often too complex. One of the reasons for this complexity is the requirement to minimize a non-convex cost function, which becomes more difficult with more complex networks. In this paper, we consider serial cascade networks affected by sensor noise. Recently, the Weighted Null-Space Fitting method has been shown to be appropriate for this setting, providing asymptotically efficient estimates without suffering from non-convexity; however, applicability of the method was subject to some conditions on the locations of sensors and excitation signals. In this paper, we drop such conditions, proposing an extension of the method that is applicable to general serial cascade networks. We formulate an algorithm that describes application of the method in a general setting, and perform a simulation study to illustrate the performance of the method, which suggests that this extension is still asymptotically efficient.

  • 11.
    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.

  • 12.
    Galrinho, Miguel
    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.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.
    Parametric Identification Using Weighted Null-Space Fitting2019In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 64, no 7, p. 2798-2813Article in journal (Refereed)
    Abstract [en]

    In identification of dynamical systems, the prediction error method with a quadratic cost function provides asymptotically efficient estimates under Gaussian noise, but in general it requires solving a nonconvex optimization problem, which may imply convergence to nonglobal minima. An alternative class of methods uses a nonparametric model as intermediate step to obtain the model of interest. Weighted null-space fitting (WNSF) belongs to this class, starting with the estimate of a nonparametric ARX model with least squares. Then, the reduction to a parametric model is a multistep procedure where each step consists of the solution of a quadratic optimization problem, which can be obtained with weighted least squares. The method is suitable for both open- and closed-loop data, and can be applied to many common parametric model structures, including output-error, ARMAX, and Box-Jenkins. The price to pay is the increase of dimensionality in the nonparametric model, which needs to tend to infinity as function of the sample size for certain asymptotic statistical properties to hold. In this paper, we conduct a rigorous analysis of these properties: namely, consistency, and asymptotic efficiency. Also, we perform a simulation study illustrating the performance of WNSF and identify scenarios where it can be particularly advantageous compared with state-of-the-art methods.

  • 13.
    Gao, Yulong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Wu, Shuang
    Hong Kong Univ Sci & Technol, Elect & Comp Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China..
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Shi, Ling
    Hong Kong Univ Sci & Technol, Elect & Comp Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China..
    Xie, Lihua
    Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore..
    Stochastic Optimal Control of Dynamic Queue Systems: A Probabilistic Perspective2018In: 2018 15TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV), IEEE , 2018, p. 837-842Conference paper (Refereed)
    Abstract [en]

    Queue overflow of a dynamic queue system gives rise to the information loss (or packet loss) in the communication buffer or the decrease of throughput in the transportation network. This paper investigates a stochastic optimal control problem for dynamic queue systems when imposing probability constraints on queue overflows. We reformulate this problem as a Markov decision process (MDP) with safety constraints. We prove that both finite-horizon and infinite-horizon stochastic optimal control for MDP with such constraints can be transformed as a linear program (LP), respectively. Feasibility conditions are provided for the finite-horizon constrained control problem. Two implementation algorithms are designed under the assumption that only the state (not the state distribution) can be observed at each time instant. Simulation results compare optimal cost and state distribution among different scenarios, and show the probability constraint satisfaction by the proposed algorithms.

  • 14.
    George, Jemin
    et al.
    US Army Res Lab, Adelphi, MD 20783 USA..
    Yi, Xinlei
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Yang, Tao
    Univ North Texas, Dept Elect Engn, Denton, TX 76203 USA..
    Distributed Robust Dynamic Average Consensus with Dynamic Event-Triggered Communication2018In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 434-439Conference paper (Refereed)
    Abstract [en]

    This paper presents the formulation and analysis of a fully distributed dynamic event-triggered communication based robust dynamic average consensus algorithm. Dynamic average consensus problem involves a networked set of agents estimating the time-varying average of dynamic reference signals locally available to individual agents. We propose an asymptotically stable solution to the dynamic average consensus problem that is robust to network disruptions. Since this robust algorithm requires continuous communication among agents, we introduce a novel dynamic event-triggered communication scheme to reduce the overall inter-agent communications. It is shown that the event-triggered algorithm is asymptotically stable and free of Zeno behavior. Numerical simulations are provided to illustrate the effectiveness of the proposed algorithm.

  • 15.
    Gonzalez, Rodrigo A.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Welsh, James S.
    Univ Newcastle, Sch Elect Engn & Comp Sci, Callaghan, NSW, Australia..
    An asymptotically optimal indirect approach to continuous-time system identification2018In: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2018, p. 638-643Conference paper (Refereed)
    Abstract [en]

    The indirect approach to continuous-time system identification consists in estimating continuous-time models by first determining an appropriate discrete-time model. For a zero-order hold sampling mechanism, this approach usually leads to a transfer function estimate with relative degree 1, independent of the relative degree of the strictly proper real system. In this paper, a refinement of these methods is developed. Inspired by the indirect prediction error method, we propose an estimator that enforces a fixed relative degree in the continuous-time transfer function estimate, and show that the estimator is consistent and asymptotically efficient. Extensive numerical simulations are put forward to show the performance of this estimator when contrasted with other indirect and direct methods for continuous-time system identification.

  • 16.
    Guo, Meng
    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.
    Andersson, Sofie
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES).
    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.
    Human-in-the-Loop Mixed-Initiative Control under Temporal Tasks2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE Computer Society, 2018, p. 6395-6400Conference paper (Refereed)
    Abstract [en]

    This paper considers the motion control and task planning problem of mobile robots under complex high-level tasks and human initiatives. The assigned task is specified as Linear Temporal Logic (LTL) formulas that consist of hard and soft constraints. The human initiative influences the robot autonomy in two explicit ways: with additive terms in the continuous controller and with contingent task assignments. We propose an online coordination scheme that encapsulates (i) a mixed-initiative continuous controller that ensures all-time safety despite of possible human errors, (ii) a plan adaptation scheme that accommodates new features discovered in the workspace and short-term tasks assigned by the operator during run time, and (iii) an iterative inverse reinforcement learning (IRL) algorithm that allows the robot to asymptotically learn the human preference on the parameters during the plan synthesis. The results are demonstrated by both realistic human-in-the-loop simulations and experiments.

  • 17. 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.

  • 18.
    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.

  • 19.
    Guo, Ziyang
    et al.
    Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China. hi, Dawei.
    Shi, Dawei
    Johansson, Karl H.
    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, Ling
    Worst-Case Innovation-Based Integrity Attacks With Side Information on mote State Estimation2019In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 6, no 1, p. 48-59Article in journal (Refereed)
    Abstract [en]

    In this paper, we study the worst-case consequence of innovation-based tegrity attacks with side information in a remote state estimation enario where a sensor transmits its measurement to a remote estimator uipped with a false-data detector. If a malicious attacker is not only le to compromise the transmitted data packet but also able to measure e system state itself, the attack strategy can be designed based on e intercepted data, the sensing data, or alternatively the combined formation. Surprisingly, we show that launching attacks using the mbined information are not always optimal. First, we characterize the ealthiness constraints for different types of attack strategies to oid being noticed by the false-data detector. Then, we derive the olution of the remote estimation error covariance in the presence of tacks, based on which the worst-case attack policies are obtained by lving convex optimization problems. Furthermore, the closed-form pressions of the worst-case attacks are obtained for scalar systems d the attack consequences are compared with the existing work to termine which strategy is more critical in deteriorating system rformance. Simulation examples are provided to illustrate the alytical results.

  • 20.
    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. 

  • 21.
    Hashimoto, Kazumune
    et al.
    Keio Univ, Dept Appl Phys & Physicoinformat, Yokohama, Kanagawa, Japan..
    Adachi, Shuichi
    Keio Univ, Dept Appl Phys & Physicoinformat, Yokohama, Kanagawa, Japan..
    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.
    Energy-aware networked control systems under temporal logic specifications2018In: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 132-139Conference paper (Refereed)
    Abstract [en]

    In recent years, event and self-triggered control have been proposed as energy-aware control strategies to expand the life-time of battery powered devices in Networked Control Systems (NCSs). In contrast to the previous works in which their control objective is to achieve stability, this paper presents a novel energy-aware control scheme for achieving high level specifications, or more specifically, temporal logic specifications. Inspired by the standard hierarchical strategy that has been proposed in the field of formal control synthesis paradigm, we propose a new abstraction procedure for jointly synthesizing control and communication strategies, such that the communication reduction in NCSs and the satisfaction of the temporal logic specifications are guaranteed. The benefits of the proposal are illustrated through a numerical example.

  • 22.
    Javid, Alireza M.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Chatterjee, Saikat
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Mutual Information Preserving Analysis of a Single Layer Feedforward Network2018In: Proceedings of the International Symposium on Wireless Communication Systems, VDE Verlag GmbH , 2018Conference paper (Refereed)
    Abstract [en]

    We construct a single layer feed forward network and analyze the constructed system using information theoretic tools, such as mutual information and data processing inequality. We derive a threshold on the number of hidden nodes required to achieve a good classification performance. Classification performance is expected to saturate as we increase the number of hidden nodes more than the threshold. The threshold is further verified by experimental studies on benchmark datasets. Index Terms-Neural networks, mutual information, extreme learning machine, invertible function.

  • 23.
    Khirirat, Sarit
    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, 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.
    Alistarh, Dan
    IST Austria, Vienna, Austria..
    Gradient compression for communication-limited convex optimization2018In: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 166-171, article id 8619625Conference paper (Refereed)
    Abstract [en]

    Data-rich applications in machine-learning and control have motivated an intense research on large-scale optimization. Novel algorithms have been proposed and shown to have optimal convergence rates in terms of iteration counts. However, their practical performance is severely degraded by the cost of exchanging high-dimensional gradient vectors between computing nodes. Several gradient compression heuristics have recently been proposed to reduce communications, but few theoretical results exist that quantify how they impact algorithm convergence. This paper establishes and strengthens the convergence guarantees for gradient descent under a family of gradient compression techniques. For convex optimization problems, we derive admissible step sizes and quantify both the number of iterations and the number of bits that need to be exchanged to reach a target accuracy. Finally, we validate the performance of different gradient compression techniques in simulations. The numerical results highlight the properties of different gradient compression algorithms and confirm that fast convergence with limited information exchange is possible.

  • 24.
    Kouyoumdjieva, Sylvia T.
    et al.
    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.
    Karlsson, Gunnar
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Experimental Evaluation of Precision of a Proximity-based Indoor Positioning System2019Conference paper (Refereed)
    Abstract [en]

    Bluetooth Low Energy beacons are small transmitters with long battery life that are considered for providing proximity-based services. In this work we evaluate experimentally the performance of a proximity-based indoor positioning system built with off-the-shelf beacons in a realistic environment. We demonstrate that the performance of the system depends on a number of factors, such as the distance between the beacon and the mobile device, the positioning of the beacon as well as the presence and positioning of obstacles such as human bodies. We further propose an online algorithm based on moving average forecasting and evaluate the algorithm in the presence of human mobility. We conclude that algorithms for proximity-based indoor positioning must be evaluated in realistic scenarios, for instance considering people and traffic on the used radio bands. The uncertainty in positioning is high in our experiments and hence the success of commercial context-aware solutions based on BLE beacons is highly dependent on the accuracy required by each application.

  • 25.
    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.

  • 26.
    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.

  • 27.
    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), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rasmussen, Lars Kildehöj
    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.
    Spectrum Sharing With Network Coding for Multiple Cognitive Users2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 1, p. 230-238Article in journal (Refereed)
    Abstract [en]

    In this paper, an intelligently cooperative communication network with cognitive users is considered, where in a primary system and a secondary system, respectively, a message is communicated to their respective receiver over a packet-based wireless link. The secondary system assists in the transmission of the primary message employing network coding, on the condition of maintaining or improving the primary performance, and is granted limited access to the transmission resources as a reward. The users in both systems exploit their previously received information in encoding and decoding the binary combined packets. Considering the priority of legitimate users, a selective cooperation mechanism is investigated and the system performance based on an optimization problem is analyzed. Both the analytical and numerical results show that the condition for the secondary system accessing the licensed spectrum resource is when the relay link performs better than the direct link of the primary transmission. We also extend the system model into a network with multiple secondary users and propose two relay selection algorithms. Jointly considering the related link qualities, a best relay selection and a best relay group selection algorithm are discussed. Overall, it is found that the throughput performance can be improved with multiple secondary users, especially with more potential users cooperating in the best relay group selection algorithm.

  • 28.
    Lindemann, Lars
    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. 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.
    Feedback control strategies for multi-agent systems under a fragment at) of signal temporal logic tasks2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 106, p. 284-293Article in journal (Refereed)
    Abstract [en]

    Multi-agent systems under temporal logic tasks have great potential due to their ability to deal with complex tasks. The control of these systems, however, poses many challenges and the majority of existing approaches result in large computational burdens. We instead propose computationally efficient and robust feedback control strategies for a class of systems that are, in a sense, feedback equivalent to single integrator systems, but where the dynamics are partially unknown for the control design. A bottom-up scenario is considered in which each agent is subject to a local task from a limited signal temporal logic fragment. Notably, the satisfaction of a local task may also depend on the behavior of other agents. We provide local continuous-time feedback control laws that, under some sufficient conditions, guarantee satisfaction of the local tasks. Otherwise, a local detection & repair scheme is proposed in combination with the previously derived feedback control laws to deal with infeasibilities, such as when local tasks are conflicting. The efficacy of the proposed method is demonstrated in simulations.

  • 29.
    Lindemann, Lars
    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. 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.
    Robust control for signal temporal logic specifications using discrete average space robustness2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 101, p. 377-387Article in journal (Refereed)
    Abstract [en]

    Control systems that satisfy temporal logic specifications have become increasingly popular due to their applicability to robotic systems. Existing control methods, however, are computationally demanding, especially when the problem size becomes too large. In this paper, a robust and computationally efficient model predictive control framework for signal temporal logic specifications is proposed. We introduce discrete average space robustness, a novel quantitative semantic for signal temporal logic, that is directly incorporated into the cost function of the model predictive controller. The optimization problem entailed in this framework can be written as a convex quadratic program when no disjunctions are considered and results in a robust satisfaction of the specification. Furthermore, we define the predicate robustness degree as a new robustness notion. Simulations of a multi-agent system subject to complex specifications demonstrate the efficacy of the proposed method.

  • 30.
    Linsenmayer, Steffen
    et al.
    Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Engineering Sciences (SCI).
    Allgoewer, Frank
    Univ Stuttgart, Inst Syst Theory & Automat Control, D-70569 Stuttgart, Germany..
    Event-Based Vehicle Coordination Using Nonlinear Unidirectional Controllers2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 4, p. 1575-1584Article in journal (Refereed)
    Abstract [en]

    This paper presents a framework to control vehicle platoons with event-based communication and nonlinear controllers. The overall goal is to achieve a platoon that moves in a desired formation with a desired velocity and the convergence to this formation should be exponential while Zeno behavior has to be excluded. The set of admissible controllers for this problem is specified by the properties that they need to guarantee. These properties will be of a form such that they can be checked locally by every vehicle itself and heterogeneous controllers as well as heterogeneous possibly nonlinear dynamics of the vehicles in the platoon are allowed. The framework is shown to work with several communication networks and the set of networks will be characterized. Modifications that are necessary to cope with additive disturbances are described and a simulation example that shows the benefits of being able to use the framework in different networks is given.

  • 31. Linsenmayer, Steffen
    et al.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. 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.
    Allgoewer, Frank
    Periodic event-triggered control for networked control systems based on non-monotonic Lyapunov functions2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 106, p. 35-46Article in journal (Refereed)
    Abstract [en]

    This article considers exponential stabilization of linear Networked Control Systems with periodic event-triggered control for a given network specification in terms of a maximum number of successive dropouts and a constant transmission delay. Based on stability results using non-monotonic Lyapunov functions for discontinuous dynamical systems, two sufficient results for stability of the general model of a linear event-triggered Networked Control System are derived. Those results are used to derive robust periodic event-triggered control strategies. First, a static triggering mechanism for the case without delay is derived. Afterwards, two dynamic triggering mechanisms are developed for the case without and with delay. It is shown how a degree of freedom, being contained in the dynamic triggering mechanisms, can be used to shape the resulting network traffic. The applied adaption technique is motivated by existing congestion control mechanisms in communication networks. The properties of the derived mechanisms are illustrated in a numerical example.

  • 32.
    Liuzza, Davide
    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.
    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 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.
    Generalized PID Synchronization of Higher Order Nonlinear Systems With a Recursive Lyapunov Approach2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 4, p. 1608-1621Article in journal (Refereed)
    Abstract [en]

    This paper investigates the problem of synchronization for nonlinear systems. Following a Lyapunov approach, we first study the global synchronization of nonlinear systems in the canonical control form with both distributed proportional-derivative and proportional-integral-derivative control actions of any order. To do so, we develop a constructive methodology and generate in an iterative way inequality constraints on the coupling matrices that guarantee the solvability of the problem or, in a dual form, provide the nonlinear weights on the coupling links between the agents such that the network synchronizes. The same methodology allows us to include a possible distributed integral action of any order to enhance the rejection of heterogeneous disturbances. The considered approach does not require any dynamic cancellation, thus preserving the original nonlinear dynamics of the agents. The results are then extended to linear and nonlinear systems admitting a canonical control transformation. Numerical simulations validate the theoretical results.

  • 33.
    Mathew, Sebin
    et al.
    McGill Univ, Dept Elect & Comp Engn, Montreal, PQ, Canada..
    Johannson, 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.
    Mahajan, Aditya
    McGill Univ, Dept Elect & Comp Engn, Montreal, PQ, Canada..
    Optimal sampling of multiple linear processes over a shared medium2018In: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1712-1718Conference paper (Refereed)
    Abstract [en]

    In many emerging applications, multiple sensors transmit their measurements to a remote estimator over a shared medium. In such a system, the optimal sampling rates at each sensor depend on the nature of the stochastic process being observed as well as the available communication capacity. Our main contribution is to show that the problem of determining optimal sampling rates may be posed as a network utility maximization problem and solved using appropriate modifications of the standard dual decomposition algorithms for network utility maximization. We present two such algorithms, one synchronous and one asynchronous, and show that under mild technical conditions, both algorithms converge to the optimal rate allocation. We present a detailed simulation study to illustrate that the asynchronous algorithm is able to adapt the sampling rate to change in the number of sensors and the available channel capacity and is robust to packet drops.

  • 34.
    Mazhar, Othmane
    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.
    Fischione, Carlo
    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.
    Hesamzadeh, Mohammad Reza
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.
    Bayesian model selection for change point detection and clustering2018In: 35th International Conference on Machine Learning, ICML 2018, International Machine Learning Society (IMLS) , 2018, p. 5497-5520Conference paper (Refereed)
    Abstract [en]

    We address a generalization of change point detection with the purpose of detecting the change locations and the levels of clusters of a piece- wise constant signal. Our approach is to model it as a nonparametric penalized least square model selection on a family of models indexed over the collection of partitions of the design points and propose a computationally efficient algorithm to approximately solve it. Statistically, minimizing such a penalized criterion yields an approximation to the maximum a-posteriori probability (MAP) estimator. The criterion is then ana-lyzed and an oracle inequality is derived using a Gaussian concentration inequality. The oracle inequality is used to derive on one hand conditions for consistency and on the other hand an adaptive upper bound on the expected square risk of the estimator, which statistically motivates our approximation. Finally, we apply our algorithm to simulated data to experimentally validate the statistical guarantees and illustrate its behavior.

  • 35. 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.

  • 36.
    Milosevic, Jezdimir
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Sandberg, Henrik
    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), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    A Security Index for Actuators Based on Perfect Undetectability: Properties and Approximation2019In: 2018 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 235-241Conference paper (Refereed)
    Abstract [en]

    A novel security index based on the definition of perfect undetectability is proposed. The index is a tool that can help a control system operator to localize the most vulnerable actuators in the network. In particular, the security index of actuator i represents the minimal number of sensors and actuators that needs to be compromised in addition to i, such that a perfectly undetectable attack is possible. A method for computing this index for small scale systems is derived, and difficulties with the index once the system is of large scale are outlined. An upper bound for the index that overcomes these difficulties is then proposed. The theoretical developments are illustrated on a numerical example. 

  • 37.
    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.

  • 38.
    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.

  • 39.
    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, 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), 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.

  • 40.
    Nikou, Alexandros
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES).
    Tumova, Jana
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES).
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES).
    Cooperative Task Planning of Multi-Agent Systems Under Timed Temporal Specifications2016In: 2016 AMERICAN CONTROL CONFERENCE (ACC), IEEE , 2016, p. 7104-7109Conference paper (Refereed)
    Abstract [en]

    In this paper the problem of cooperative task planning of multi-agent systems when timed constraints are imposed to the system is investigated. We consider timed constraints given by Metric Interval Temporal Logic (MITL). We propose a method for automatic control synthesis in a twostage systematic procedure. With this method we guarantee that all the agents satisfy their own individual task specifications as well as that the team satisfies a team global task specification.

  • 41.
    Olofsson, Per E.
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Brandt, Ludwig
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Magnusson, Klas E. G.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Frisk, Thomas
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Jaldén, Joakim
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Önfelt, Björn
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    A collagen-based microwell migration assay to study NK-target cell interactions2019In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 10672Article in journal (Refereed)
    Abstract [en]

    Natural killer (NK) cell cytotoxicity in tissue is dependent on the ability of NK cells to migrate through the extracellular matrix (ECM) microenvironment. Traditional imaging studies of NK cell migration and cytotoxicity have utilized 2D surfaces, which do not properly reproduce the structural and mechanical cues that shape the migratory response of NK cells in vivo. Here, we have combined a microwell assay that allows long-term imaging and tracking of small, well-defined populations of NK cells with an interstitial ECM-like matrix. The assay allows for long-term imaging of NK-target cell interactions within a confined 3D volume. We found marked differences in motility between individual cells with a small fraction of the cells moving slowly and being confined to a small volume within the matrix, while other cells moved more freely. A majority of NK cells also exhibited transient variation in their motility, alternating between periods of migration arrest and movement. The assay could be used as a complement to in vivo imaging to study human NK cell heterogeneity in migration and cytotoxicity.

  • 42.
    Owrang, Arash
    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.
    Jansson, Magnus
    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.
    A Model Selection Criterion for High-Dimensional Linear Regression2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 13, p. 3436-3446Article in journal (Refereed)
    Abstract [en]

    Statistical model selection is a great challenge when the number of accessible measurements is much smaller than the dimension of the parameter space. We study the problem of model selection in the context of subset selection for high-dimensional linear regressions. Accordingly, we propose a new model selection criterion with the Fisher information that leads to the selection of a parsimonious model from all the combinatorial models up to some maximum level of sparsity. We analyze the performance of our criterion as the number of measurements grows to infinity, as well as when the noise variance tends to zero. In each case, we prove that our proposed criterion gives the true model with a probability approaching one. Additionally, we devise a computationally affordable algorithm to conduct model selection with the proposed criterion in practice. Interestingly, as a side product, our algorithm can provide the ideal regularization parameter for the Lasso estimator such that Lasso selects the true variables. Finally, numerical simulations are included to support our theoretical findings.

  • 43.
    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.

  • 44.
    Pirani, Mohammad
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hashemi, E.
    Fidan, B.
    Simpson-Porco, J. W.
    Sandberg, Henrik
    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), Automatic Control.
    Resilient Estimation and Control on k-Nearest Neighbor Platoons: A Network-Theoretic Approach2018In: IFAC-PapersOnLine, Vol. 51, no 23, p. 22-27Article in journal (Refereed)
    Abstract [en]

    This paper is concerned with the network-theoretic properties of so-called k-nearest neighbor intelligent vehicular platoons, where each vehicle communicates with k vehicles, both in front and behind. The network-theoretic properties analyzed in this paper play major roles in quantifying the resilience and robustness of three generic distributed estimation and control algorithms against communication failures and disturbances, namely resilient distributed estimation, resilient distributed consensus, and robust network formation. Based on the results for the connectivity measures of the k-nearest neighbor platoon, we show that extending the traditional platooning topologies (which were only based on interacting with nearest neighbors) to k-nearest neighbor platoons increases the resilience of distributed estimation and control algorithms to both communication failures and disturbances. 

  • 45. Pu, Y.
    et al.
    Zhu, J.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Ramchandran, K.
    Tomlin, C. J.
    Coded Control over Lossy Networks2018In: Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 3602-3608Conference paper (Refereed)
    Abstract [en]

    We consider a networked control system with an unreliable feedback link from the sensor to the controller. Specifically, a discrete-time linear system is to be controlled via a packet-drop channel where multiple packets are transmitted at each time instance. We propose a coded control scheme that jointly designs the coding strategy, which mitigates the channel unreliability, and the control strategy, which stabilizes the unstable system. This scheme is based on the idea of successive refinement, that more important system states (or linear combinations thereof) should be better protected against the unreliable channel. The proposed scheme is simple to implement as it uses a static encoder and decoder/controller, in the sense that all encoding and decoding procedures do not require information from previous time steps. Furthermore, we compare it with two other static schemes and show that our approach strikes a good balance between optimality and complexity.

  • 46.
    Ren, Xiaoqiang
    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.
    Mo, Y.
    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.
    Secure Static State Estimation: A Large Deviation Approach2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 23, p. 289-294Article in journal (Refereed)
    Abstract [en]

    This paper studies static state estimation based on measurements from a set of sensors, a subset of which can be compromised by an attacker. The measurements from a compromised sensor can be manipulated arbitrarily by the adversary. A new notion is adopted to indicate the performance of an estimator, that is, the asymptotic exponential rate, with which the worst-case probability of estimate lying outside certain ball centered at the true underlying state goes to zero. An optimal estimator, which computes Chebyshev centers and only utilizes the information contained in the averaged measurements, is proposed. Numerical examples are given to elaborate the results.

  • 47. 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.

  • 48.
    Risuleo, Riccardo Sven
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Bottegal, G.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Approximate Maximum-likelihood Identification of Linear Systems from Quantized Measurements⁎2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 724-729Article in journal (Refereed)
    Abstract [en]

    We analyze likelihood-based identification of systems that are linear in the parameters from quantized output data; in particular, we propose a method to find approximate maximum-likelihood and maximum-a-posteriori solutions. The method consists of appropriate least-squares projections of the middle point of the active quantization intervals. We show that this approximation maximizes a variational approximation of the likelihood and we provide an upper bound for the approximation error. In a simulation study, we compare the proposed method with the true maximum-likelihood estimate of a finite impulse response model. 

  • 49.
    Risuleo, Riccardo Sven
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Bottegal, Giulio
    Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Modeling and identification of uncertain-input systems2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 105, p. 130-141Article in journal (Refereed)
    Abstract [en]

    We present a new class of models, called uncertain-input models, that allows us to treat system-identification problems in which a linear system is subject to a partially unknown input signal. To encode prior information about the input or the linear system, we use Gaussian-process models. We estimate the model from data using the empirical Bayes approach: the hyperparameters that characterize the Gaussian-process models are estimated from the marginal likelihood of the data. We propose an iterative algorithm to find the hyperparameters that relies on the EM method and results in decoupled update steps. Because in the uncertain-input setting neither the marginal likelihood nor the posterior distribution of the unknowns is tractable, we develop an approximation approach based on variational Bayes. As part of the contribution of the paper, we show that this model structure encompasses many classical problems in system identification such as Hammerstein models, blind system identification, and cascaded linear systems. This connection allows us to build a systematic procedure that applies effectively to all the aforementioned problems, as shown in the numerical simulations presented in the paper.

  • 50.
    Sandberg, Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Control theory for practical cyber-physical security: Extended abstract2018In: CPSS 2018 - Proceedings of the 4th ACM Workshop on Cyber-Physical System Security, Co-located with ASIA CCS 2018, Association for Computing Machinery, Inc , 2018, p. 25-26Conference paper (Refereed)
    Abstract [en]

    In this talk, we discuss how control theory can contribute to the analysis and design of secure cyber-physical systems. We start by reviewing conditions for undetectable false-data injection attacks on feedback control systems. In particular, we highlight how a physical understanding of the controlled process can guide us in the allocation of protective measures. We show that protecting only a few carefully selected actuators or sensors can give indirect protection to many more components. We then illustrate how such analysis is exploited in the design of a resilient control scheme for a microgrid energy management system.

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