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  • 1.
    Biel, Martin
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Farokhi, Farhad
    Sandberg, Henrik
    SiMpLIfy: A toolbox for structured model reduction2015In: 2015 European Control Conference, ECC 2015, Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1159-1164Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a toolbox for structured model reduction developed for MATLAB. In addition to structured model reduction methods using balanced realizations of the subsystems, we introduce a numerical algorithm for structured model reduction using a subgradient optimization algorithm. We briefly present the syntax for the toolbox and its features. Finally, we demonstrate the applicability of various model reduction methods in the toolbox on a structured mass-spring mechanical system.

  • 2.
    Farokhi, Farhad
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Decentralized Control Design with Limited Plant Model Information2012Licentiate thesis, monograph (Other academic)
    Abstract [en]

    Large-scale control systems are often composed of several smaller interconnected units. For these systems, it is common to employ local controllers, which observe and act locally. At the heart of common control design procedures for distributed systems lies the often implicit assumption that the designer has access to the global plant model information when designing a local controller. However, there are several reasons why such plant model information would not be globally known. One reason could be that the designer wants the parameters of each local controller to only depend on local model information, so that the controllers are not modified if the model parameters of a particular subsystem change. It might also be the case that the design of each local controller is done by individual designers with no access to the global plant model, for instance, due to the fact that the designers refuse to share their model information since they consider it private. This class of problems, which we refer to as limited model information control design, is the topic of the thesis. First, we investigate the achievable closed-loop performance of discrete-time linear time-invariant plants under a separable quadratic cost performance with structured static state-feedback controllers. To do so, we introduce control design strategies as mappings, which construct controllers by accessing the plant model information in a constrained way according to a given design graph. We compare control design strategies using the competitive ratio as a performance metric, that is, we compare the worst case control performance for a given design strategy normalized with the optimal control performance based on full model information. An explicit minimizer of the competitive ratio is sought. As this minimizer might not be unique, we further search for the ones that are undominated, that is, there is no other control design strategy in the set of limited model information design strategies with a better closed-loop performance for all possible plants while maintaining the same worst-case ratio. We study the trade-off between the amount of model information exploited by a control design strategy and the best possible closed-loop performance. We generalize this setup to structured dynamic state-feedback controllers for H_2-performance. Surprisingly, the optimal control design strategy with limited model information is still a static one. This is the case even though the optimal decentralized state-feedback controller with full model information is dynamic. Finally, we discuss the design of dynamic controllers for disturbance accommodation under limited model information. This problem is of special interest because the best limited model information control design in this case is a dynamic control design strategy. The optimal controller can be separated into a static feedback law and a dynamic disturbance observer. For constant disturbances, it is shown that this structure corresponds to proportional-integral control.

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  • 3.
    Farokhi, Farhad
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Decentralized Control of Networked Systems: Information Asymmetries and Limitations2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Designing local controllers for networked systems is challenging, because in these systems each local controller can often access only part of the overall information on system parameters and sensor measurements. Traditional control design cannot be easily applied due to the unconventional information patterns, communication network imperfections, and design procedure complexities. How to control large-scale systems is of immediate societal importance as they appear in many emerging applications, such as intelligent transportation systems, smart grids, and energy-efficient buildings. In this thesis, we make three contributions to the problem of designing networked controller under information asymmetries and limitations.

    In the first contribution, we investigate how to design local controllers to optimize a cost function using only partial knowledge of the model governing the system. Specifically, we derive some fundamental limitations in the closed-loop performance when the design of each controller only relies on local plant model information. Results are characterized in the structure of the networked system as well as in the available model information. Both deterministic and stochastic formulations are considered for the closed-loop performance and the available information. In the second contribution of the thesis, we study decision making in transportation systems using heterogeneous routing and congestion games. It is shown that a desirable global behavior can emerge from simple local strategies used by the drivers to choose departure times and routes. Finally, the third contribution is a novel stochastic sensor scheduling policy for ad-hoc networked systems, where a varying number of control loops are active at any given time. It is shown that the policy provides stochastic guarantees for the network resources dynamically allocated to each loop.

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    Thesis
  • 4.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Adaptive control design under structured model information limitation: A cost-biased maximum-likelihood approach2015In: Systems & control letters (Print), ISSN 0167-6911, E-ISSN 1872-7956, Vol. 75, p. 8-13Article in journal (Refereed)
    Abstract [en]

    Networked control strategies based on limited information about the plant model usually result in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst-case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. We show that an adaptive controller, inspired by a controller proposed by Campi and Kumar, with limited plant model information, asymptotically achieves the closed-loop performance of the optimal centralized controller with full model information for almost any plant. Therefore, there exists, at least, one adaptive control design strategy with limited plant model information that can achieve a competitive ratio equal to one. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed-loop performance measure is the ergodic mean of a quadratic function of the state and control input.

  • 5.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Using piecewise-constant congestion taxing policy in repeated routing games2015In: SIAM Conference on Control and Its Applications 2015, 2015, p. 274-281Conference paper (Refereed)
    Abstract [en]

    We consider repeated routing games with piecewise-constant congestion taxing in which a central planner sets and announces the congestion taxes for fixed windows of time in advance. Specifically, congestion taxes are calculated using marginal congestion pricing based on the flow of the vehicles on each road prior to the beginning of the taxing window. The piecewise-constant taxing policy in motivated by that users or drivers may dislike fast-changing prices and that they also prefer prior knowledge of the prices. We prove that the multiplicative update rule converges to a socially optimal flow when using vanishing step sizes. Considering that the algorithm cannot adapt itself to a changing environment when using vanishing step sizes, we propose using constant step sizes in this case. Then, however, we can only prove the convergence of the dynamics to a neighborhood of the socially optimal flow (with its size being of the order of the selected step size).

  • 6.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Game-Theoretic Framework for Studying Truck Platooning Incentives2013In: Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC 2013), IEEE conference proceedings, 2013, p. 1253-1260Conference paper (Refereed)
    Abstract [en]

    An atomic congestion game with two types of agents, cars and trucks, is used to model the traffic flow on a road over certain time intervals. In this game, the drivers make a trade-off between the time they choose to use the road, the average velocity of the flow at that time, and the dynamic congestion tax that they are paying to use the road. The trucks have platooning capabilities and therefore, have an incentive for using the road at the same time as their peers. The dynamics and equilibria of this game-theoretic model for the interaction between car traffic and truck platooning incentives are investigated. We use traffic data from Stockholm to validate the modeling assumptions and extract reasonable parameters for the simulations. We perform a comprehensive simulation study to understand the influence of various factors, such as the percentage of the trucks that are equipped with platooning devices on the properties of the pure strategy Nash equilibrium that is learned using a joint strategy fictitious play.

  • 7.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Study of Truck Platooning Incentives Using a Congestion Game2015In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 16, no 2, p. 581-595, article id 6847185Article in journal (Refereed)
    Abstract [en]

    We introduce an atomic congestion game with two types of agents, namely, cars and trucks, to model the traffic flow on a road over various time intervals of the day. Cars maximize their utility by finding a tradeoff between the time they choose to use the road, the average velocity of the flow at that time, and the dynamic congestion tax that they pay for using the road. In addition to these terms, the trucks have an incentive for using the road at the same time as their peers because they have platooning capabilities, which allow them to save fuel. The dynamics and equilibria of this game-theoretic model for the interaction between car traffic and truck platooning incentives are investigated. We use traffic data from Stockholm, Sweden, to validate parts of the modeling assumptions and extract reasonable parameters for the simulations. We use joint strategy fictitious play and average strategy fictitious play to learn a pure strategy Nash equilibrium of this game. We perform a comprehensive simulation study to understand the influence of various factors, such as the drivers' value of time and the percentage of the trucks that are equipped with platooning devices, on the properties of the Nash equilibrium.

  • 8.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dynamic Control Design Based on Limited Model Information2011In: Proceedings of the 49th Annual Allerton Conference on Communication, Control, and Computing, 2011, p. 1576-1583Conference paper (Refereed)
    Abstract [en]

    The design of optimal H_2 dynamic controllers for interconnected linear systems using limited plant model information is considered. Control design strategies based on various degrees of model information are compared using the competitive ratio as a performance metric, that is, the worst case control performance for a given design strategy normalized with the optimal control performance based on full model information. An explicit minimizer of the competitive ratio is found. It is shown that this control design strategy is not dominated by any other strategy with the same amount of model information. The result applies to a class of system interconnections and design information characterized through given plant, control, and design graphs.

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    IR-EE-RT_2011_090
  • 9.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Investigating the Interaction Between Traffic Flow and Vehicle Platooning Using a Congestion Game2014In: Proceedings of the 19th IFAC World Congress, 2014 / [ed] Boje, Edward; Xia, Xiaohua, 2014, p. 4170-4177Conference paper (Refereed)
    Abstract [en]

    We consider a congestion game with two types of agents to describe the traffic flow on a road at various time intervals in each day. The first type of agents (cars) maximize a utility which is determined by a sum of a penalty for using the road at a time other than their preferred time interval, the average velocity of the traffic flow, and the congestion tax. The second type of agents (trucks or heavy-duty vehicles) can benefit from using the road together with other second-type agents. This is because the trucks can form platoons to save fuel through reducing the air drag force. We study a Nash equilibrium of this game to study the interaction between the traffic flow and the platooning incentives. We prove that the introduced congestion game does not admit a potential function unless we devise an appropriate congestion taxing policy. We use joint strategy fictitious play and average strategy fictitious play to learn a pure strategic Nash equilibrium of this congestion game. Lastly, we demonstrate the developed results on a numerical example using data from a highway segment in Stockholm.

  • 10.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Limited Model Information Control Design for Linear Discrete-Time Systems with Stochastic Parameters2012In: 2012 IEEE 51st Annual Conference on Decision And Control (CDC), IEEE , 2012, p. 855-861Conference paper (Refereed)
    Abstract [en]

    We design optimal local controllers for large-scale networked systems using exact local model information and statistical beliefs about the model of the rest of the system. We study the value of model information in control design using the closed-loop performance degradation caused by the lack of full model information in the control design procedure. This performance degradation is captured using the ratio of the cost of the optimal controller with limited model information over the cost of the optimal controller with full model information. Both finite-horizon and infinite-horizon cost functions are considered. A numerical example illustrates the developed approach.

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  • 11.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal control design under limited model information for discrete-time linear systems with stochastically-varying parameters2015In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 60, no 3, p. 684-699Article in journal (Refereed)
    Abstract [en]

    The value of plant model information available in the control design process is discussed. We design optimal state-feedback controllers for interconnected discrete-time linear systems with stochastically-varying parameters. The parameters are assumed to be independently and identically distributed random variables in time. The design of each controller relies only on (i) exact local plant model information and (ii) statistical beliefs about the model of the rest of the system. We consider both finite-horizon and infinite-horizon quadratic cost functions. The optimal state-feedback controller is derived in both cases. The optimal controller is shown to be linear in the state and to depend on the model parameters and their statistics in a particular way. Furthermore, we study the value of model information in optimal control design using the performance degradation ratio which is defined as the supremum (over all possible initial conditions) of the ratio of the cost of the optimal controller with limited model information scaled by the cost of the optimal controller with full model information. An upper bound for the performance degradation ratio is presented for the case of fully-actuated subsystems. Comparisons are made between designs based on limited, statistical, and full model information. Throughout the paper, we use a power network example to illustrate concepts and results.

  • 12.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal Control Design under Structured Model Information Limitation Using Adaptive Algorithms2012Article in journal (Refereed)
    Abstract [en]

    Networked control strategies based on limited information about the plant model usually results in worse closed-loop performance than optimal centralized control with full plant model information. Recently, this fact has been established by utilizing the concept of competitive ratio, which is defined as the worst case ratio of the cost of a control design with limited model information to the cost of the optimal control design with full model information. In this paper, we show that with an adaptive networked controller with limited plant model information, it is indeed possible to achieve a competitive ratio equal to one. We show that an adaptive controller introduced by Campi and Kumar asymptotically achieves closed-loop performance equal to the optimal centralized controller with full model information. The plant model considered in the paper belongs to a compact set of stochastic linear time-invariant systems and the closed loop performance measure is the ergodic mean of a quadratic function of the state and control input. We illustrate the applicability of the results numerically on a vehicle platooning problem.

  • 13.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Stochastic Sensor Scheduling for Networked Control Systems2014In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 59, no 5, p. 1147-1162Article in journal (Refereed)
    Abstract [en]

    Optimal sensor scheduling with applications to networked estimation and control systems is considered. We model sensor measurement and transmission instances using jumps between states of a continuous-time Markov chain. We introduce a cost function for this Markov chain as the summation of terms depending on the average sampling frequencies of the subsystems and the effort needed for changing the parameters of the underlying Markov chain. By minimizing this cost function through extending Brockett's recent approach to optimal control of Markov chains, we extract an optimal scheduling policy to fairly allocate the network resources among the control loops. We study the statistical properties of this scheduling policy in order to compute upper bounds for the closed-loop performance of the networked system, where several decoupled scalar subsystems are connected to their corresponding estimator or controller through a shared communication medium. We generalize the estimation results to observable subsystems of arbitrary order. Finally, we illustrate the developed results numerically on a networked system composed of several decoupled water tanks.

  • 14.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Stochastic sensor scheduling with application to networked control2013In: 2013 American Control Conference (ACC), Institute of Electrical and Electronics Engineers (IEEE) , 2013, p. 2325-2332Conference paper (Refereed)
    Abstract [en]

    We consider stochastic sensor scheduling with application to networked control systems. We model sampling instances (in a networked system) using jumps between states of a continuous-time Markov chain. We introduce a cost function for this Markov chain which is composed of terms depending on the average sampling frequencies of the subsystems and the effort needed for changing the parameters of the underlying Markov chain. By extending Brockett's recent contribution in optimal control of Markov chains, we extract an optimal scheduling policy to fairly allocate network resources (i.e., access to the network) among the control loops. We apply this scheduling policy to a networked control system composed of several scalar decoupled subsystems and compute upper bounds for their closed-loop performance. We illustrate the developed results numerically on a networked system composed of several water tanks.

  • 15.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Krichene, Walid
    University of California at Berkeley.
    Alexandre M., Bayen
    University of California at Berkeley.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    When Do Potential Functions Exist in Heterogeneous Routing Games?2014Report (Other academic)
    Abstract [en]

    We study a heterogeneous routing game in which vehicles might belong to more than one type. The type determines the cost of traveling along an edge as a function of the flow of various types of vehicles over that edge. We relax the assumptions needed for the existence of a Nash equilibrium in this heterogeneous routing game. We extend the available results to present necessary and sufficient conditions for the existence of a potential function. We characterize a set of tolls that guarantee the existence of a potential function when only two types of users are participating in the game. We present an upper bound for the price of anarchy (i.e., the worst-case ratio of the social cost calculated for a Nash equilibrium over the social cost for a socially optimal flow) for the case in which only two types of players are participating in a game with affine edge cost functions. A heterogeneous routing game with vehicle platooning incentives is used as an example throughout the article to clarify the concepts and to validate the results.

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    fulltext
  • 16.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Krichene, Walid
    University of California at Berkeley.
    Bayen, Alexandre M.
    University of California at Berkeley.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Heterogeneous Routing Game2013In: 2013 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013, IEEE conference proceedings, 2013, p. 448-455Conference paper (Refereed)
    Abstract [en]

    Most literature on routing games make the assumption that drivers or vehicles are of the same type and, hence, experience the same latency or cost when traveling along the edges of the network. In contrast, in this article, we propose a heterogeneous routing game in which each driver or vehicle belongs to a certain type. The type determines the cost of traveling along an edge as a function of the flow of all types of drivers or vehicles over that edge. We examine the existence of a Nash equilibrium in this heterogeneous routing game. We study the conditions for which the problem of finding a Nash equilibrium can be posed as a convex optimization problem and is therefore numerically tractable. Numerical simulations are presented to validate the results.

  • 17.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Department of Aerospace Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA..
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Control Design with Limited Model Information2011In: Proceedings of the 2011 American Control Conference, AACC , 2011, p. 4697-4704Conference paper (Refereed)
    Abstract [en]

    We introduce the family of limited model information control design methods, which construct controllers by accessing the plant’s model in a constrained way, according to a given design graph. This class generalizes the notion of communication-less control design methods recently introduced by one of the authors, which construct each sub-controller using only local plant model information. We study the tradeoff between the amount of model information exploited by a control design method and the quality of controllers it can produce. In particular, we quantify the benefit (in terms of the competitive ratio and domination metrics) of giving the control designer access to the global interconnection structure of the plant-to-be-controlled, in addition to local model information.

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    fulltext
  • 18.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Department of Aerospace Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA..
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Decentralized Disturbance Accommodation with Limited Plant Model Information2013In: SIAM Journal of Control and Optimization, ISSN 0363-0129, E-ISSN 1095-7138, Vol. 51, no 2, p. 1543-1573Article in journal (Refereed)
    Abstract [en]

    The design of optimal disturbance accommodation and servomechanism controllers with limited plant model information is studied in this paper. We consider discrete-time linear time-invariant systems that are fully actuated and composed of scalar subsystems, each of which is controlled separately and influenced by a scalar disturbance. Each disturbance is assumed to be generated by a system with known dynamics and unknown initial conditions. We restrict ourselves to control design methods that produce structured dynamic state feedback controllers where each subcontroller, at least, has access to the state measurements of those subsystems that can affect its corresponding subsystem. The performance of such control design methods is compared using a metric called the competitive ratio, which is the worst-case ratio of the cost of a given control design strategy to the cost of the optimal control design with full model information. We find an explicit minimizer of the competitive ratio and show that it is undominated, that is, there is no other control design strategy that performs better for all possible plants while having the same worst-case ratio. This optimal controller can be separated into a static feedback law and a dynamic disturbance observer. For step disturbances, it is shown that this structure corresponds to proportional-integral control.

  • 19.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Department of Aerospace Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA..
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Decentralized H2 Control Design with Limited Model Information2011Report (Other academic)
    Abstract [en]

    This paper deals with designing optimal decentralized H2 controller for interconnected discrete-time time-invariant systems with limited model information. We adapt the notion of limited model information designs to handle the dynamic H2 controllers. The best decentralized control design strategy, in terms of the competitive ratio and domination metrics, is found for different acyclic plant graphs when the control graph is a super-graph of the plant graph.

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    TRITA-EE_2011_064
  • 20.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Department of Aerospace Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA..
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    On Designing Optimal Controllers with Limited Model Information2010Report (Other academic)
    Abstract [en]

    We introduce the family of limited model information designs, which construct controllers by accessing the plant's model in a constrained manner. We investigate the closed loop performance of the best controller that they can produce. For a class of linear discrete-time, time invariant plants, we show that there exists a limited model information control design which results in a controller whose performance is in a bounded neighborhood of the optimal control design and we show that this controller is the best controller that one can design with limited information about the plant model. We investigate the plant model structure and the model information on this neighborhood.

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    TRITA-EE_2010_039
  • 21.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Department of Aerospace Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA..
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal Disturbance Accommodation with Limited Model Information2012In: 2012 American Control Conference (ACC), IEEE Computer Society, 2012, p. 4757-4764Conference paper (Refereed)
    Abstract [en]

    The design of optimal dynamic disturbance accommodation controller with limited model information is considered. We adapt the family of limited model information control design strategies, defined earlier by the authors, to handle dynamic controllers. This family of limited model information design strategies construct subcontrollers distributively by accessing only local plant model information. The closed-loop performance of the dynamic controllers that they can produce are studied using a performance metric called the competitive ratio which is the worst case ratio of the cost a control design strategy to the cost of the optimal control design with full model information.

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  • 22.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Department of Aerospace Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA..
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal Structured Static State-Feedback Control Design with Limited Model Information for Fully-Actuated Systems2013In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 49, no 2, p. 326-337Article in journal (Refereed)
    Abstract [en]

    We introduce the family of limited model information control design methods, which construct controllers by accessing the plant's model in a constrained way, according to a given design graph. We investigate the closed-loop performance achievable by such control design methods for fully-actuated discrete-time linear time-invariant systems, under a separable quadratic cost. We restrict our study to control design methods which produce structured static state feedback controllers, where each subcontroller can at least access the state measurements of those subsystems that affect its corresponding subsystem. We compute the optimal control design strategy (in terms of the competitive ratio and domination metrics) when the control designer has access to the local model information and the global interconnection structure of the plant-to-be-controlled. Finally, we study the trade-off between the amount of model information exploited by a control design method and the best closed-loop performance (in terms of the competitive ratio) of controllers it can produce.

  • 23. Farokhi, Farhad
    et al.
    Liang, Kuo-Yun
    KTH, School of Electrical Engineering (EES), Automatic Control. Scania CV AB, Sweden.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Cooperation Patterns between Fleet Owners for Transport Assignments2015In: 2015 IEEE CONFERENCE ON CONTROL AND APPLICATIONS (CCA 2015), IEEE conference proceedings, IEEE , 2015, p. 1124-1129Conference paper (Refereed)
    Abstract [en]

    We study cooperation patterns between the heavy- duty vehicle fleet owners to reduce their costs, improve their fuel efficiency, and decrease their emissions. We consider a distributed cooperation pattern in which the fleet owners can communicate directly with each other to form alliances. A centralized cooperation pattern is studied in which the fleet owners pay to subscribe to a third-party service provider that pairs their vehicles for cooperation. The effects of various pricing strategies on the behaviour of fleet owners and their inclusiveness are analyzed. It is shown that the fleet size has an essential role. 

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  • 24.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sandberg, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Robust Control-Design Method Using Bode’s Ideal Transfer Function2011In: Proceedings of the 19th Mediterranean Conference on Control and Automation, IEEE conference proceedings, 2011, p. 712-717Conference paper (Refereed)
    Abstract [en]

    We propose a method for designing loop-shaping controllers using Bode's ideal transfer function. Bode's ideal transfer function is introduced using fractional calculus. The ideal loop transfer function is approximated using the first generation CRONE approximation, and then implemented by means of Hinfinity-optimization followed by closed-loop controller order reduction of the resulting controller. The design method is confirmed to be powerful and robust by simulating on a flexible transmission system.

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    IR-EE-RT_2011_087
  • 25.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sandberg, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Complexity Reduction for Parameter-Dependent Linear Systems2013In: 2013 American Control Conference (ACC), American Automatic Control Council , 2013, p. 2624-2630Conference paper (Refereed)
    Abstract [en]

    We present a complexity reduction algorithm for a family of parameter-dependent linear systems when the system parameters belong to a compact semi-algebraic set. This algorithm potentially describes the underlying dynamical system with fewer parameters or state variables. To do so, it minimizes the distance (i.e., $H_\infty$-norm of the difference) between the original system and its reduced version. We present a sub-optimal solution to this problem using sum-of-squares optimization methods. We present the results for both continuous-time and discrete-time systems. Lastly, we illustrate the applicability of our proposed algorithm on numerical examples.

  • 26.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sandberg, Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Optimal H-Infinity Control Design under Model Information Limitations and State Measurement Constraints2013In: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC), IEEE conference proceedings, 2013, p. 6218-6225Conference paper (Refereed)
    Abstract [en]

    We present a suboptimal control design algorithm for a family of continuous-time parameter-dependent linear systems that are composed of interconnected subsystems. We are interested in designing the controller for each subsystem such that it only utilizes partial state measurements (characterized by a directed graph called the control graph) and limited model parameter information (characterized by the design graph). The algorithm is based on successive local minimizations and maximizations (using the subgradients) of the H∞-norm of the closed-loop transfer function with respect to the controller gains and the system parameters. We use a vehicle platooning example to illustrate the applicability of the results.

  • 27.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Shames, Iman
    University of Melbourne, Australia.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Distributed MPC Via Dual Decomposition and Alternating Direction Method of Multipliers2013In: Distributed Model Predictive Control Made Easy / [ed] Rudy R. Negenborn and Jose M. Maestre, Springer, 2013Chapter in book (Refereed)
    Abstract [en]

    A conventional way to handle model predictive control (MPC) problems distributedly is to solve them via dual decomposition and gradient ascent. However, at each time-step, it might not be feasible to wait for the dual algorithm to converge. As a result, the algorithm might be needed to be terminated prematurely. One is then interested to see if the solution at the point of termination is close to the optimal solution and when one should terminate the algorithm if a certain distance to optimality is to be guaranteed. In this chapter, we look at this problem for distributed systems under general dynamical and performance couplings, then, we make a statement on validity of similar results where the problem is solved using alternative direction method of multipliers.

  • 28.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Shirazinia, Amirpasha
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Networked Estimation Using Sparsifying Basis Prediction2013In: IFAC Proceedings Volumes, 2013, p. 174-181Conference paper (Refereed)
    Abstract [en]

    We present a framework for networked state estimation, where systems encode their (possibly high dimensional) state vectors using a mutually agreed basis between the system and the estimator (in a remote monitoring unit). The basis sparsifies the state vectors, i.e., it represents them using vectors with few non-zero components, and as a result, the systems might need to transmit only a fraction of the original information to be able to recover the non-zero components of the transformed state vector. Hence, the estimator can recover the state vector of the system from an under-determined linear set of equations. We use a greedy search algorithm to calculate the sparsifying basis. Then, we present an upper bound for the estimation error. Finally, we demonstrate the results on a numerical example.

  • 29.
    Farokhi, Farhad
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Teixeira, Andre M. H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Gaussian Cheap Talk Game with Quadratic Cost Functions: When Herding Between Strategic Senders is a Virtue2014In: 2014 AMERICAN CONTROL CONFERENCE (ACC), 2014Conference paper (Refereed)
    Abstract [en]

    We consider a Gaussian cheap talk game with quadratic cost functions. The cost function of the receiver is equal to the estimation error variance, however, the cost function of each senders contains an extra term which is captured by its private information. Following the cheap talk literature, we model this problem as a game with asymmetric information. We start by the single sender case in which the receiver also has access to a noisy but honest side information in addition to the message transmitted by a strategic sender. We generalize this setup to multiple sender case. For the multiple sender case, we observe that if the senders are not herding (i. e., copying each other policies), the quality of the receiver's estimation degrades rapidly as the number of senders increases.

  • 30.
    Larsson, Martin
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Lindberg, Jonas
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Lycke, Jens
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hansson, Karl
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Khakulov, Aziz
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Ringh, Emil
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Svensson, Fredrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Tjernberg, Isak
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Alam, Assad
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Araujo, Jose
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Farokhi, Farhad
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ghadimi, Euhanna
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Teixeira, Andre
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Towards an Indoor Testbed for Mobile Networked Control Systems2011Conference paper (Refereed)
    Abstract [en]

    In this paper, we consider the design of an indoor testbed composed of multiple aerial and ground unmanned vehicles for experimentation in Mobile Networked Control Systems. Taking several motivational aspects from both research and education into account, we propose an architecture to cope with the scale and mobility aspects of the overall system. Currently, the testbed is composed of several low-cost ARdrones quadrotors, small-scale heavy duty vehicles, wireless sensor nodes and a vision-based localization system. As an example, the automatic control of an ARdrone is shown.

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  • 31.
    Tanaka, Takashi
    et al.
    Massachusetts Institute of Technology (MIT).
    Farokhi, Farhad
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Langbort, Cedric
    Department of Aerospace Engineering and the Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Illinois, USA..
    A faithful distributed implementation of dual decomposition and average consensus algorithms2013In: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC), 2013, p. 2985-2990Conference paper (Refereed)
    Abstract [en]

    We consider large scale cost allocation problems and consensus seeking problems for multiple agents in which agents are suggested to collaborate in a distributed algorithm to find a solution. If agents are strategic and minimize their own individual cost rather than the global social cost, they are endowed with an incentive not to follow the intended algorithm, unless the tax/subsidy mechanism is carefully designed. Inspired by the classical Vickrey-Clarke-Groves mechanism and more recent algorithmic mechanism design theory, we propose a tax mechanism that incentivises agents to faithfully implement the intended algorithm. In particular, a new notion of asymptotic incentive compatibility is introduced to characterize a desirable property of such class of mechanisms. The proposed class of tax mechanisms provides a sequence of mechanisms that gives agents a diminishing incentive to deviate from suggested algorithm.

1 - 31 of 31
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