By Topic

Automatic Control, IEEE Transactions on

Issue 11 • Date Nov. 2013

Filter Results

Displaying Results 1 - 25 of 36
  • Table of Contents

    Publication Year: 2013 , Page(s): C1 - C4
    Save to Project icon | Request Permissions | PDF file iconPDF (138 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Automatic Control publication information

    Publication Year: 2013 , Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (135 KB)  
    Freely Available from IEEE
  • Scanning the issue

    Publication Year: 2013 , Page(s): 2713 - 2714
    Save to Project icon | Request Permissions | PDF file iconPDF (135 KB)  
    Freely Available from IEEE
  • Attack Detection and Identification in Cyber-Physical Systems

    Publication Year: 2013 , Page(s): 2715 - 2729
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3839 KB) |  | HTML iconHTML  

    Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial control processes, and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. In this paper: (i) we propose a mathematical framework for cyber-physical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (ii) we design centralized and distributed attack detection and identification monitors. Finally, we validate our findings through compelling examples. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Synergistic Hybrid Feedback for Global Rigid-Body Attitude Tracking on \hbox { SO }(3)^{\ast } {ssr {SO}}(3)^{\ast }

    Publication Year: 2013 , Page(s): 2730 - 2742
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4132 KB) |  | HTML iconHTML  

    In this paper, we propose two hybrid feedbacks based on “synergistic” potential functions to achieve robust global asymptotic tracking of rigid-body attitude, a task that is impossible by classical state feedback-be it smooth, nonsmooth, or periodic-due to the topological structure of the special orthogonal group. Both hybrid feedbacks are based upon a proportional-derivative structure where the proportional term is generated from a finite family of control-induced artificial potential energies and the derivative term is due to a damping injection. In a patient-yet-greedy fashion, the hybrid feedback hysteretically switches to the minimum control-induced artificial potential energy in a finite family. The synergy property-which requires that for each undesirable critical point of each potential energy, there exists a lower potential energy in the family-guarantees the globality of robust asymptotic tracking. The first hybrid feedback is the natural extension of existing PD controllers and results in discontinuous jumps in the control signal due to a direct switch the potential energy. Using a backstepping procedure, we design a second hybrid feedback that smooths the jumps in the control torque by dynamically interpolating between the switching potential-energy terms. We show that while the class of “modified trace functions” is not wide enough to generate a “centrally synergistic” potential function, relaxing the centrality assumption allows one to construct a synergistic family and we provide explicit guidelines for doing so. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Nonuniform coverage control on the line

    Publication Year: 2013 , Page(s): 2743 - 2755
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2685 KB) |  | HTML iconHTML  

    This paper investigates control laws allowing mobile, autonomous agents to optimally position themselves on the line for distributed sensing in a nonuniform field. We show that a simple static control law, based only on local measurements of the field by each agent, drives the agents close to the optimal positions after the agents execute in parallel a number of sensing/movement/computation rounds that is essentially quadratic in the number of agents. Further, we exhibit a dynamic control law which, under slightly stronger assumptions on the capabilities and knowledge of each agent, drives the agents close to the optimal positions after the agents execute in parallel a number of sensing/communication/computation/movement rounds that is essentially linear in the number of agents. Crucially, both algorithms are fully distributed and robust to unpredictable loss and addition of agents. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Coordinated One-Step Optimal Distributed State Prediction for a Networked Dynamical System

    Publication Year: 2013 , Page(s): 2756 - 2771
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5641 KB) |  | HTML iconHTML  

    A new recursive one-step state prediction procedure is derived for a networked dynamic system. Under the coordination of a collaboration unit that provides optimal update gains for each individual subsystem utilizing merely system parameters, this predictor estimates plant's local states based only on local system output measurements. This estimator can be easily realized in a distributed way, and can also be simply scaled to systems with a large amount of subsystems, provided it has enough communication and storage capacities. It is proved that when prediction error variances are adopted in performance comparisons, the optimal gain matrix is usually unique. Recursive and explicit expressions are derived for both this optimal gain matrix and the covariance matrix of the corresponding prediction errors. The optimal gain matrix for every subsystem in this distributed recursive predictor has been shown to be equal to that of the well known Kalman filter utilizing only local system output measurements, which makes it possible to robustify this state predictor using a sensitivity penalization approach. Numerical simulation results illustrate that prediction accuracy of the suggested procedure may sometimes be as good as that of the lumped Kalman filter. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Designing Optimal Deadlock Avoidance Policies for Sequential Resource Allocation Systems Through Classification Theory: Existence Results and Customized Algorithms

    Publication Year: 2013 , Page(s): 2772 - 2787
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3213 KB) |  | HTML iconHTML  

    A recent line of work has sought the implementation of the maximally permissive deadlock avoidance policy (DAP) for a broad class of complex resource allocation systems (RAS) as a classifier that gives effective and parsimonious representation to the dichotomy of the underlying behavioral space into the admissible and inadmissible subspaces defined by that policy. The work presented in this paper complements the past developments in this area by providing 1) succinct conditions regarding the possibility of expressing the aforementioned classifier as a set of linear inequalities in the RAS state variables, and 2) an efficient customized algorithm for the synthesis of pertinent nonlinear classifiers that implement the target DAP with minimum run-time computational overhead, in the case that a linear-classifier-based representation of this policy is not possible. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Internal Model Principle for Linear Systems With Periodic State Jumps

    Publication Year: 2013 , Page(s): 2788 - 2802
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5162 KB) |  | HTML iconHTML  

    This paper deals with the problem of output regulation for a class of hybrid linear SISO systems and exosystems whose dynamics have jumps according to the value of a clock variable. The problem of designing controllers embedding an hybrid internal model of the switching exosystem in order to achieve the regulation objective is addressed. Key concepts and tools well known in the field of output regulation for continuous-time systems, such as the concept of steady-state response, of regulator equations and the internal model property, are thus generalized to the hybrid setting. Emphasis is placed on internal models and stabilizers that are robust to uncertainties entering both in the flow and jump dynamics of the hybrid controlled system. Time-varying and time-independent design principles are presented. Simulation results show the effectiveness of the proposed solutions in meaningful cases. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Infinite Horizon Performance Bounds for Uncertain Constrained Systems

    Publication Year: 2013 , Page(s): 2803 - 2817
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4095 KB) |  | HTML iconHTML  

    We present a new method to bound the performance of controllers for uncertain linear systems with mixed state and input constraints and bounded disturbances. We take as a performance metric either an expected-value or minimax discounted cost over an infinite horizon, and provide a method for computing a lower bound on the achievable performance of any causal control policy in either case. Our lower bound is compared to an upper performance bound provided by restricting the choice of controller to one that is affine in the observed disturbances, and we show that the two bounds are closely related. In particular, the lower bounds have a natural interpretation in terms of affine control policies that are optimal for a problem with a restricted disturbance set. We show that our performance bounds can be computed via solution of a finite-dimensional convex optimization problem, and provide numerical examples to illustrate the efficacy of our method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Distributed Control Strategy for Reactive Power Compensation in Smart Microgrids

    Publication Year: 2013 , Page(s): 2818 - 2833
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3400 KB) |  | HTML iconHTML  

    We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We then consider the specific problem of commanding the microgenerators connected to a microgrid, in order to achieve the optimal injection of reactive power. For this task, we design a randomized, leader-less, gossip-like optimization algorithm. We show how a distributed approach is possible, where microgenerators need to have only a partial knowledge of the problem parameters and of the state, and can perform only local measurements. For the proposed algorithm, we provide conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that, in radial networks, the best performance is achieved when we command cooperation among microgenerators that are neighbors in the electric topology. Numerical simulations are included to validate both the proposed model and the analytic results about the performance of the proposed algorithm. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Moving Horizon Estimation for Large-Scale Interconnected Systems

    Publication Year: 2013 , Page(s): 2834 - 2847
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3403 KB) |  | HTML iconHTML  

    We present computationally efficient centralized and distributed moving horizon estimation (MHE) methods for large-scale interconnected systems, that are described by sparse banded or sparse multibanded system matrices. Both of these MHE methods are developed by approximating a solution of the MHE problem using the Chebyshev approximation method. By exploiting the sparsity of this approximate solution we derive a centralized MHE method, which computational complexity and storage requirements scale linearly with the number of local subsystems of an interconnected system. Furthermore, on the basis of the approximate solution of the MHE problem, we develop a novel, distributed MHE method. This distributed MHE method estimates the state of a local subsystem using only local input-output data. In contrast to the existing distributed algorithms for the state estimation of large-scale systems, the proposed distributed MHE method is not relying on the consensus algorithms and has a simple analytic form. We have studied the stability of the proposed MHE methods and we have performed numerical simulations that confirm our theoretical results. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Circulant Rational Covariance Extension Problem: The Complete Solution

    Publication Year: 2013 , Page(s): 2848 - 2861
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (3893 KB) |  | HTML iconHTML  

    The rational covariance extension problem to determine a rational spectral density given a finite number of covariance lags can be seen as a matrix completion problem to construct an infinite-dimensional positive-definite Toeplitz matrix the northwest corner of which is given. The circulant rational covariance extension problem considered in this paper is a modification of this problem to partial stochastic realization of periodic stationary process, which are better represented on the discrete unit circle rather than on the discrete real line . The corresponding matrix completion problem then amounts to completing a finite-dimensional Toeplitz matrix that is circulant. Another important motivation for this problem is that it provides a natural approximation, involving only computations based on the fast Fourier transform, for the ordinary rational covariance extension problem, potentially leading to an efficient numerical procedure for the latter. The circulant rational covariance extension problem is an inverse problem with infinitely many solutions in general, each corresponding to a bilateral ARMA representation of the underlying periodic process. In this paper, we present a complete smooth parameterization of all solutions and convex optimization procedures for determining them. A procedure to determine which solution that best matches additional data in the form of logarithmic moments is also presented. View full abstract»

    Open Access
  • Adaptive Tracking Games for Coupled Stochastic Linear Multi-Agent Systems: Stability, Optimality and Robustness

    Publication Year: 2013 , Page(s): 2862 - 2877
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (5208 KB) |  | HTML iconHTML  

    Distributed adaptive tracking-type games are investigated for a class of coupled stochastic linear multi-agent systems with uncertainties of unknown structure parameters, external stochastic disturbances, unmodeled dynamics, and unknown agents' interactions. The control goal is to make the states of all the agents converge to a desired function of the population state average (PSA). Due to the fact that only local information is available for each agent, the control is distributed. For the time-invariant parameter case, the extended least-squares algorithm, Nash certainty equivalence (NCE) principle, and certainty equivalence (CE) principle are used to estimate the unknown parameters and the PSA term, and to design adaptive control, respectively. Under some mild conditions, it is shown that the closed-loop system is almost surely uniformly stable with respect to the population number N; the estimate for the PSA term is strongly consistent; the adaptive control is almost surely an asymptotic Nash equilibrium. When the dynamics of each agent contains time-varying parameters and unmodeled dynamics, the projected least mean square (LMS) algorithm, NCE principle, and CE principle are adopted to estimate the unknown time-varying parameters, and the unknown PSA term, and to design robust adaptive control, respectively. In addition to stability of the closed-loop system and consistency of the PSA estimate, the control law is shown to be robust Nash equilibrium with respect to the unmodeled dynamics, the variation of the unknown parameters, and the external disturbances. Two numerical examples are given to illustrate the methods and results of this paper. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Modified Riccati Transformation for Decentralized Computation of the Viability Kernel Under LTI Dynamics

    Publication Year: 2013 , Page(s): 2878 - 2892
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3904 KB) |  | HTML iconHTML  

    Computing the viability kernel is key in providing guarantees of safety and proving existence of safety-preserving controllers for constrained dynamical systems. Current numerical techniques that approximate this construct suffer from a complexity that is exponential in the dimension of the state. We study conditions under which a linear time-invariant (LTI) system can be suitably decomposed into lower dimensional subsystems so as to admit a conservative computation of the viability kernel in a decentralized fashion in subspaces. We then present an isomorphism that imposes these desired conditions, most suitably on two-time-scale systems. Decentralized computations are performed in the transformed coordinates, yielding a conservative approximation of the viability kernel in the original state space. Significant reduction of complexity can be achieved, allowing the previously inapplicable tools to be employed for treatment of higher dimensional systems. We show the results on two examples including a 6-D system. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Inertial Vector Measurements Based Velocity-Free Attitude Stabilization

    Publication Year: 2013 , Page(s): 2893 - 2898
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1350 KB) |  | HTML iconHTML  

    The existing rigid body attitude controllers (without angular velocity measurements) involve explicitly the attitude in the feedback. Unfortunately, there does not exist any sensor that directly measures the orientation of a rigid body (without any estimation procedure). Therefore the attitude must be generated from the available sensors via some attitude determination (estimation) algorithms. The most recent and efficient attitude estimation algorithms rely on the body vector measurements and the angular velocity (which is assumed to be unavailable in velocity-free attitude controllers). To overcome this circular reasoning-like problem, we propose a velocity-free attitude stabilization control scheme relying solely on body vector measurements. Moreover, the proposed control law is a priori bounded and does not lead to the so-called unwinding phenomenon1 encountered in some unit-quaternion based attitude control schemes. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robust Reduced-order H Output-Feedback Control of Retarded Stochastic Linear Systems

    Publication Year: 2013 , Page(s): 2898 - 2904
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1592 KB) |  | HTML iconHTML  

    A method for designing reduced-order output-feedback controllers for linear time-invariant retarded systems with state-multiplicative Wiener-type noise is introduced, which achieves a minimum bound on the H performance level. A cost function is defined that is the expected value of the standard H performance cost with respect to the stochastic parameters. A solution is thus obtained, for the reduced-order H output-feedback control problem, for the stationary case, via the input-output approach where the system is replaced by a non-retarded one, that contains deterministic norm-bounded uncertainties. The results achieved for the nominal case are extended to the uncertain case where the system matrices reside in a given polytope. A numerical example, taken from the field of aircraft control, is given that demonstrates the applicability of the theory developed. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Global Adaptive Regulation of Uncertain Nonlinear Systems in Output Feedback Form

    Publication Year: 2013 , Page(s): 2904 - 2909
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1261 KB) |  | HTML iconHTML  

    Minimum phase uncertain nonlinear systems in output feedback form are considered: they are subject to disturbances and/or uncertainties and are required to track reference signals. Both disturbances and references are generated by an exosystem whose model and order are uncertain. Assuming that the regulator problem has a solution, but with no a priori assumption on the required control input (e.g. no `immersion' assumption), a global robust error feedback regulator is explicitly computed which includes an adaptive internal model and a nonlinear stabilizing control, on the basis of known bounding functions for the uncertain system nonlinearities. The regulation error tends to a residual set which decreases as the reference input modeling error due to the internal model choice decreases. If the adaptive internal model can generate the required unknown control input, global asymptotic regulation is achieved. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Linear-Exponential-Quadratic Gaussian Control

    Publication Year: 2013 , Page(s): 2910 - 2911
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (442 KB) |  | HTML iconHTML  

    In this technical note an optimal control problem for a linear stochastic system with Brownian motion and a cost that is an exponential of a quadratic functional of the state and the control is solved by obtaining explicitly an optimal control and the optimal cost. While this solution has been previously obtained, the approach given here is direct and elementary and does not use the well known solution methods of the Hamilton-Jacobi-Bellman equation or the stochastic maximum principle. The approach given here presents a basic insight in the solution by providing a simple explanation for the additional term in the Riccati equation for the optimal control as compared to the Riccati equation for the linear-quadratic Gaussian control problem. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Distributed Output-Feedback Control of Nonlinear Multi-Agent Systems

    Publication Year: 2013 , Page(s): 2912 - 2917
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1298 KB) |  | HTML iconHTML  

    This technical note presents a cyclic-small-gain approach to distributed output-feedback control of nonlinear multi-agent systems. Through novel distributed observer and control law designs, the closed-loop multi-agent system is transformed into a large-scale system composed of input-to-output stable (IOS) subsystems, the IOS gains of which can be appropriately designed. By guaranteeing the IOS of the closed-loop multi-agent system with the recently developed cyclic-small-gain theorem, the outputs of the controlled agents can be driven to within an arbitrarily small neighborhood of the desired agreement value under bounded external disturbances. Moreover, if the system is disturbance-free, then asymptotic convergence can be achieved. Interestingly, the closed-loop distributed system is also robust to bounded time-delays of exchanged information. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Minimum-Energy Filtering for Attitude Estimation

    Publication Year: 2013 , Page(s): 2917 - 2921
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (861 KB) |  | HTML iconHTML  

    In this work, we study minimum-energy filtering for attitude kinematics with vectorial measurements using Mortensen's approach. The exact form of a minimum-energy attitude observer is derived and is shown to depend on the Hessian of the value function of an associated optimal control problem. A suitably chosen matrix representation of the Hessian operator leads to a Riccati equation that approximates a minimum-energy attitude filter. An extended version of the proposed approximate filter is included for a situation where there is slowly time-varying bias in the gyro measurements. A unit quaternion version of the proposed filter is derived and shown to outperform the multiplicative extended Kalman filter (MEKF) for situations with large initialization errors or large measurement errors. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Robust Sampled – Data Control of Switched Affine Systems

    Publication Year: 2013 , Page(s): 2922 - 2928
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1849 KB) |  | HTML iconHTML  

    This technical note considers the stabilization problem for switched affine systems with a sampled-data switching law. The switching law is assumed to be a function of the system state at sampling instants and the sampling interval may be subject to variations or uncertainty. We provide a robust switching law design that takes into account the sampled-data implementation and uncertainties. The problem is addressed from the continuous-time point of view. The method is illustrated by numerical examples. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A New Extension of Newton Algorithm for Nonlinear System Modelling Using RBF Neural Networks

    Publication Year: 2013 , Page(s): 2929 - 2933
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (921 KB) |  | HTML iconHTML  

    Model performance and convergence rate are two key measures for assessing the methods used in nonlinear system identification using Radial Basis Function neural networks. A new extension of the Newton algorithm is proposed to further improve these two aspects by extending the results of recently proposed continuous forward algorithm (CFA) and hybrid forward algorithm (HFA). Computational complexity analysis confirms its efficiency, and numerical examples show that it converges faster and potentially outperforms CFA and HFA. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Designing Output-Feedback Predictive Controllers by Reverse-Engineering Existing LTI Controllers

    Publication Year: 2013 , Page(s): 2934 - 2939
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1403 KB) |  | HTML iconHTML  

    An approach to designing a constrained output-feedback predictive controller that has the same small-signal properties as a pre-existing output-feedback linear time invariant controller is proposed. Systematic guidelines are proposed to select an appropriate (non-unique) realization of the resulting state observer. A method is proposed to transform a class of offset-free reference tracking controllers into the combination of an observer, steady-state target calculator and predictive controller. The procedure is demonstrated with a numerical example. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Controller Design and the Gauss–Lucas Theorem

    Publication Year: 2013 , Page(s): 2940 - 2944
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1032 KB) |  | HTML iconHTML  

    In this technical note, we demonstrate how the classical Gauss-Lucas theorem can aid in the determination of stabilizing controllers for feedback systems. Moreover, we show how to apply the Gauss-Lucas theorem in the construction of new necessary conditions for Schur and Hurwitz stability. The results are used to derive new bounds on the stability margins and performance of control systems. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

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

Full Aims & Scope

Meet Our Editors

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