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Automatic Control, IEEE Transactions on

Issue 4 • Date April 2014

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Displaying Results 1 - 25 of 36
  • Table of contents

    Publication Year: 2014 , Page(s): C1 - C4
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  • IEEE Transactions on Automatic Control publication information

    Publication Year: 2014 , Page(s): C2
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    Freely Available from IEEE
  • Scanning The Issue

    Publication Year: 2014 , Page(s): 833 - 834
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  • Risk-Sensitive Mean-Field Games

    Publication Year: 2014 , Page(s): 835 - 850
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4652 KB) |  | HTML iconHTML  

    In this paper, we study a class of risk-sensitive mean-field stochastic differential games. We show that under appropriate regularity conditions, the mean-field value of the stochastic differential game with exponentiated integral cost functional coincides with the value function satisfying a Hamilton -Jacobi- Bellman (HJB) equation with an additional quadratic term. We provide an explicit solution of the mean-field best response when the instantaneous cost functions are log-quadratic and the state dynamics are affine in the control. An equivalent mean-field risk-neutral problem is formulated and the corresponding mean-field equilibria are characterized in terms of backward-forward macroscopic McKean-Vlasov equations, Fokker-Planck-Kolmogorov equations, and HJB equations. We provide numerical examples on the mean field behavior to illustrate both linear and McKean-Vlasov dynamics. View full abstract»

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  • LQ Control for Coordinated Linear Systems

    Publication Year: 2014 , Page(s): 851 - 862
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3037 KB) |  | HTML iconHTML  

    Coordinated linear systems are a special class of hierarchical linear systems, with a strict top-to-bottom information structure. The LQ problem over all structure-preserving static state feedbacks is discussed. The overall control problem separates into conditionally independent subproblems, a numerical approach to their solution is derived, and the behavior and performance of the resulting control law are illustrated in examples. View full abstract»

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  • On the Robustness of Nominal Nonlinear Minimum-Time Control and Extension to Non-Robustly Controllable Target Sets

    Publication Year: 2014 , Page(s): 863 - 875
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3784 KB) |  | HTML iconHTML  

    This work deals with the analysis and the design of minimum-time control laws for a class of nonlinear discrete-time dynamical systems characterized by K-continuous transition maps and bounded control inputs. In the paper, it is shown that the reachability properties of the target set, even if not robust positively controllable in one state transition, can be exploited to assess the existence of a robust positively controllable set including the target in its interior. This result allows the formulation of a robustified minimum-time control policy, based on iterated online optimizations and guaranteeing the ultimate boundedness of the state-trajectories in the presence of bounded uncertainties, even if the target set is not robust positively controllable. View full abstract»

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  • Rapidly Exponentially Stabilizing Control Lyapunov Functions and Hybrid Zero Dynamics

    Publication Year: 2014 , Page(s): 876 - 891
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3909 KB) |  | HTML iconHTML  

    This paper addresses the problem of exponentially stabilizing periodic orbits in a special class of hybrid models-systems with impulse effects-through control Lyapunov functions. The periodic orbit is assumed to lie in a C1 submanifold Z that is contained in the zero set of an output function and is invariant under both the continuous and discrete dynamics; the associated restriction dynamics are termed the hybrid zero dynamics. The orbit is furthermore assumed to be exponentially stable within the hybrid zero dynamics. Prior results on the stabilization of such periodic orbits with respect to the full-order dynamics of the system with impulse effects have relied on input-output linearization of the dynamics transverse to the zero dynamics manifold. The principal result of this paper demonstrates that a variant of control Lyapunov functions that enforce rapid exponential convergence to the zero dynamics surface, Z, can be used to achieve exponential stability of the periodic orbit in the full-order dynamics, thereby significantly extending the class of stabilizing controllers. The main result is illustrated on a hybrid model of a bipedal walking robot through simulations and is utilized to experimentally achieve bipedal locomotion via control Lyapunov functions. View full abstract»

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  • A New Family of High-Resolution Multivariate Spectral Estimators

    Publication Year: 2014 , Page(s): 892 - 904
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3628 KB) |  | HTML iconHTML  

    In this paper, we extend the Beta divergence family to multivariate power spectral densities. Similarly to the scalar case, we show that it smoothly connects the multivariate Kullback-Leibler divergence with the multivariate Itakura-Saito distance. We successively study a spectrum approximation problem, based on the Beta divergence family, which is related to a multivariate extension of the THREE spectral estimation technique. It is then possible to characterize a family of solutions to the problem. An upper bound on the complexity of these solutions will also be provided. Finally, we will show that the most suitable solution of this family depends on the specific features required from the estimation problem. View full abstract»

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  • Accelerated Dual Descent for Network Flow Optimization

    Publication Year: 2014 , Page(s): 905 - 920
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3936 KB) |  | HTML iconHTML  

    We present a fast distributed solution to the convex network flow optimization problem. Our approach uses a family of dual descent algorithms that approximate the Newton direction to achieve faster convergence rates than existing distributed methods. The approximate Newton directions are obtained through matrix splitting techniques and sparse Taylor approximations of the inverse Hessian. We couple this descent direction with a distributed line search algorithm which requires the same information as our descent direction to compute. We show that, similarly to conventional Newton methods, the proposed algorithm exhibits super-linear convergence within a neighborhood of the optimal value. Numerical experiments corroborate that convergence times are between one to two orders of magnitude faster than existing distributed optimization methods. A connection with recent developments that use consensus to compute approximate Newton directions is also presented. View full abstract»

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  • Partial-Information State-Based Optimization of Partially Observable Markov Decision Processes and the Separation Principle

    Publication Year: 2014 , Page(s): 921 - 936
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3980 KB) |  | HTML iconHTML  

    We propose a partial-information state based approach to the optimization of the long-run average performance in a partially observable Markov decision process (POMDP). In this approach, the information history is summarized (at least partially) by a (or a few) statistic(s), not necessary sufficient, called a partial-information state, and actions depend on the partial-information state, rather than system states. We first propose the “single-policy based comparison principle,” under which we derive an HJB-type of optimality equation and policy iteration for the optimal policy in the partial-information-state based policy space. We then introduce the Q-sufficient statistics and show that if the partial-information state is Q-sufficient, then the optimal policy in the partial-information state based policy space is optimal in the space of all feasible information state based policies. We show that with some further conditions the well-known separation principle holds. The results are obtained by applying the direct comparison based approach initially developed for discrete event dynamic systems. View full abstract»

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  • Nonanticipative Rate Distortion Function and Relations to Filtering Theory

    Publication Year: 2014 , Page(s): 937 - 952
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (6808 KB) |  | HTML iconHTML  

    The relation between nonanticipative rate distortion function (RDF) and filtering theory is discussed on abstract spaces. The relation is established by imposing a realizability constraint on the reconstruction conditional distribution of the classical RDF. Existence of the extremum solution of the nonanticipative RDF is shown using weak *-convergence on appropriate topology. The extremum reconstruction conditional distribution is derived in closed form, for the case of stationary processes. The realization of the reconstruction conditional distribution which achieves the infimum of the nonanticipative RDF is described. Finally, an example is presented to illustrate the concepts. View full abstract»

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  • Unified Analysis of Iterative Learning and Repetitive Controllers in Trial Domain

    Publication Year: 2014 , Page(s): 953 - 965
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2734 KB) |  | HTML iconHTML  

    While iterative learning control (ILC) and repetitive control (RC) have much ground in common, they fundamentally differ in the initial conditions at each repetition. This difference has lead to distinct analysis techniques, hereby clouding the interrelations between both control strategies. To facilitate the transfer of results, this paper presents a unified approach to ILC and RC. Both control problems are formulated in the trial domain using so-called system lifting. For a given system, the corresponding ILC and RC trial-domain models differ, and a thorough system theoretic analysis and comparison of these models is performed. To illustrate the value of a unified formulation of ILC and RC, the analysis of the most commonly used ILC and RC structures is harmonized. This analysis reveals central differences and similarities between various stability, monotonic convergence and steady-state performance conditions. View full abstract»

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  • On Most Permissive Observers in Dynamic Sensor Activation Problems

    Publication Year: 2014 , Page(s): 966 - 981
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5032 KB) |  | HTML iconHTML  

    We consider the problem of dynamic sensor activation for fault diagnosis of discrete event systems modeled by finite state automata under the constraint that any fault must be diagnosed within no more than K + 1 events after its occurrence, a property called K-diagnosability. We begin by defining an appropriate notion of information state for the problem and defining dynamic versions of the projection operator and information state evolution. We continue by showing that the problem can be reduced to that of state disambiguation. Then we define the most permissive observer (MPO) structure that contains all the solutions to the problem, and we prove results showing that maintaining the K-diagnosability property is equivalent to satisfying the extended specification of the state disambiguation problem. We then prove a monotonicity property of the extended specification, and show that this allows us to reduce our information state, which in turn allows us to significantly reduce the complexity of our solution. Putting all of our results together, we obtain a MPO with a size complexity of O(2|X|(K+2)|X|2|E|), compared with O(2|X|2 ·K ·2|E|) for the previous approach, where X and E are, respectively, the sets of states and events of the automaton to diagnose. Finally, we provide an algorithm for constructing the most permissive observer and demonstrate its scalability through simulation. View full abstract»

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  • Control for Safety Specifications of Systems With Imperfect Information on a Partial Order

    Publication Year: 2014 , Page(s): 982 - 995
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (5461 KB) |  | HTML iconHTML  

    In this paper, we consider the control problem for uncertain systems with imperfect information, in which an output of interest must be kept outside an undesired region (the bad set) in the output space. The state, input, output, and disturbance spaces are equipped with partial orders. The system dynamics are either input/output order preserving with output in R2 or given by the parallel composition of input/output order preserving dynamics each with scalar output. We provide necessary and sufficient conditions under which an initial set of possible system states is safe, that is, the corresponding outputs are steerable away from the bad set with open loop controls. A closed loop control strategy is explicitly constructed, which guarantees that the current set of possible system states, as obtained from an estimator, generates outputs that never enter the bad set. The complexity of algorithms that check safety of an initial set of states and implement the control map is quadratic with the dimension of the state space. The algorithms are illustrated on two application examples: a ship maneuver to avoid an obstacle and safe navigation of an helicopter among buildings. View full abstract»

    Open Access
  • Necessary and Sufficient LMI Conditions for Stability and Performance Analysis of 2-D Mixed Continuous-Discrete-Time Systems

    Publication Year: 2014 , Page(s): 996 - 1007
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3064 KB) |  | HTML iconHTML  

    This paper proposes necessary and sufficient conditions for stability and performance analysis of 2-D mixed continuous-discrete-time systems that can be checked with convex optimization, in particular linear matrix inequalities (LMIs). Specifically, the first contribution of the paper is a condition for exponential stability based on the introduction of a complex Lyapunov function depending polynomially on a parameter and on the use of the Gram matrix method. It is shown that this condition is sufficient for any chosen degree of the complex Lyapunov function, and necessary for an a priori known degree. The second contribution is a non-Lyapunov condition for exponential stability based on eigenvalue products. This condition is necessary and sufficient, and has the advantage of requiring a significantly smaller computational burden for achieving necessity. Lastly, the third contribution is to show how upper bounds on the H∞ norm of 2-D mixed continuous-discrete-time systems can be obtained through a semidefinite program based on complex Lyapunov functions. A necessary and sufficient condition is provided for establishing the tightness of the found upper bounds. View full abstract»

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  • A Heuristic Approach to Static Output-Feedback Controller Synthesis With Restricted Frequency-Domain Specifications

    Publication Year: 2014 , Page(s): 1008 - 1014
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1228 KB) |  | HTML iconHTML  

    Restricted frequency-domain specifications (RFDSs) are often encountered in control system design. In this technical note, we investigate the problem of static output-feedback (SOF) controller synthesis subject to a class of RFDSs. Motivated by the generalized Kalman-Yakubovich-Popov lemma and the two-stage strategy for SOF stabilization, a necessary and sufficient condition for the existence of an SOF controller satisfying an RFDS is first derived, and is then used to construct a heuristic approach to computing the SOF gain. The heuristic approach includes two stages: first designing an initial full-information (FI) controller and then computing an SOF gain. Moreover, a heuristic method is proposed to optimize the initial FI controller. Numerical examples are presented to demonstrate the effectiveness of the proposed design method. The main contribution of the technical note is extending the two-stage idea to SOF controller synthesis subject to RFDSs. In addition, the underlying relationship between some typical two-stage approaches to SOF stabilization is revealed. View full abstract»

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  • Distinguishability of Discrete-Time Nonlinear Systems

    Publication Year: 2014 , Page(s): 1014 - 1020
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1395 KB) |  | HTML iconHTML  

    This note considers the problem of identifying a discrete-time nonlinear system, within a finite family of possible models, from data sequences of a finite length. The problem is approached by resorting to the notion of output distinguishability. This amounts to asking whether output data sequences generated by different models can be distinguished from one another. A number of results are presented with examples. Connections with conditions for linear systems are established. View full abstract»

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  • Self-Excited Limit Cycles in an Integral-Controlled System With Backlash

    Publication Year: 2014 , Page(s): 1020 - 1025
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (939 KB) |  | HTML iconHTML  

    In this technical note, we study the properties of self-excited limit cycles in an integral-controlled system containing a play operator. A Newton-Raphson algorithm is formulated to calculate the limit cycles, and we prove that the amplitude and period of these limit cycles have linear relationships to system parameters. These results are confirmed in simulation, where we demonstrate the ability to predict the properties of the limit cycles. View full abstract»

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  • Particle Filtering Framework for a Class of Randomized Optimization Algorithms

    Publication Year: 2014 , Page(s): 1025 - 1030
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1207 KB) |  | HTML iconHTML  

    We reformulate a deterministic optimization problem as a filtering problem, where the goal is to compute the conditional distribution of the unobserved state given the observation history. We prove that in our formulation the conditional distribution converges asymptotically to a degenerate distribution concentrated on the global optimum. Hence, the goal of searching for the global optimum can be achieved by computing the conditional distribution. Since this computation is often analytically intractable, we approximate it by particle filtering, a class of sequential Monte Carlo methods for filtering, which has proven convergence in “tracking” the conditional distribution. The resultant algorithmic framework unifies some randomized optimization algorithms and provides new insights into their connection. View full abstract»

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  • On Feasibility, Stability and Performance in Distributed Model Predictive Control

    Publication Year: 2014 , Page(s): 1031 - 1036
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1032 KB) |  | HTML iconHTML  

    In distributed model predictive control (DMPC), where a centralized optimization problem is solved in distributed fashion using dual decomposition, it is important to keep the number of iterations in the solution algorithm small. In this technical note, we present a stopping condition to such distributed solution algorithms that is based on a novel adaptive constraint tightening approach. The stopping condition guarantees feasibility of the optimization problem and stability and a prespecified performance of the closed-loop system. View full abstract»

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  • Efficient Foraging Strategies in Multi-Agent Systems Through Curve Evolutions

    Publication Year: 2014 , Page(s): 1036 - 1041
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (896 KB) |  | HTML iconHTML  

    In nature, communal hunting is often performed by predators charging through an aggregation of prey. Variations exist in the geometric shape of the charging front depending on the particulars of the feeding strategy. Inspired by biology, this technical note investigates these geometric variations, and we model the predator front as a curve moving through a prey density. Using variational arguments for evolving the curve shape, we optimize the shape of the front. View full abstract»

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  • Multivariable MRAC Design Without Gain Symmetry Conditions Using a Stabilizing Multiplier

    Publication Year: 2014 , Page(s): 1041 - 1047
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1492 KB) |  | HTML iconHTML  

    A new multivariable MRAC design for plants of arbitrary relative degree, which does not require a stringent symmetry assumption related with the plant high frequency gain matrix, is presented. In contrast to previous results, the new solution does not involve additional parametrization and filtering, being thus close in structure and complexity to conventional solutions. Instead of the fragile symmetry assumption, a less restrictive and robust condition is required, which can be achieved using a multiplier. View full abstract»

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  • Stable Internally Positive Representations of Continuous Time Systems

    Publication Year: 2014 , Page(s): 1048 - 1053
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1956 KB) |  | HTML iconHTML  

    An Internally Positive Representation (IPR) of a non-positive system is a positive system that, under suitable input, state and output transformations, exactly replicates the behavior of the original system. Any construction method of an IPR necessarily introduces additional natural modes, which in some cases are unstable. In a previous paper the authors have presented a method that provides a stable IPR if and only if the eigenvalues of the original system lie in a specific sector of the open left-half complex plane. In this technical note a new technique is proposed that overcomes such a limitation, and provides a stable IPR for any stable system, although in some cases the dimension of the IPR must be large in order to guarantee its stability. Although, for simplicity, the method is only illustrated for single-input single-output systems with distinct eigenvalues, it also applies to multi-input multi-output systems with multiple eigenvalues. View full abstract»

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  • On Discrete-Time Convergence for General Linear Multi-Agent Systems Under Dynamic Topology

    Publication Year: 2014 , Page(s): 1054 - 1059
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1177 KB) |  | HTML iconHTML  

    This note aims to develop the nonnegative matrix theory, in particular the product properties of infinite row-stochastic matrices, which is widely used for multiple integrator agents, to deal with the convergence analysis of general discrete-time linear multi-agent systems (MASs). With the proposed approach, it is finally shown both theoretically and by simulation that the consensus for all the agents can be reached exponentially fast under relaxed conditions, i.e. the individual uncoupled system is allowed to be strictly unstable (in the discrete-time sense) and it is only required that the joint of the communication topologies has a spanning tree frequently enough. Moreover, a least convergence rate as well as an upper bound for the strictly unstable mode, which are independent of the switching mode of the system, are specified as well. View full abstract»

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  • Continuous-Discrete Time Observers for a Class of MIMO Nonlinear Systems

    Publication Year: 2014 , Page(s): 1060 - 1065
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1199 KB) |  | HTML iconHTML  

    This technical note addresses the observer design problem for a class of continuous-time dynamical systems with non-uniformly sampled measurements. More specifically, we propose an observer that runs in continuous-time with an output error correction term that is updated in a mixed continuous-discrete fashion. The proposed observer is actually an impulsive system since it is described by a set of differential equations with instantaneous state impulses corresponding to the measured samples and their estimates. Nevertheless, we shall show that such an impulsive system can be put under the form of a hybrid system composed of a continuous-time high gain observer coupled with an inter-sample output predictor. Two design features of the proposed observer are worth emphasizing. Firstly, the observer calibration is achieved through the tuning of a scalar design parameter. Secondly, the exponential convergence to zero of the observation error is established under a well-defined condition on the maximum value of the sampling partition diameter. Simulations results involving a flexible joint robot arm are given in order to highlight the performance of the proposed observer. View full abstract»

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Aims & Scope

In the IEEE Transactions on Automatic Control, the IEEE Control Systems Society publishes high-quality papers on the theory, design, and applications of control engineering.  Two types of contributions are regularly considered

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Meet Our Editors

Editor-in-Chief
P. J. Antsaklis
Dept. Electrical Engineering
University of Notre Dame