By Topic

Automatic Control, IEEE Transactions on

Issue 1 • Date Jan. 2009

Filter Results

Displaying Results 1 - 25 of 26
  • Table of contents

    Page(s): C1
    Save to Project icon | Request Permissions | PDF file iconPDF (38 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Automatic Control publication information

    Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (37 KB)  
    Freely Available from IEEE
  • Scanning the issue

    Page(s): 1 - 2
    Save to Project icon | Request Permissions | PDF file iconPDF (37 KB)  
    Freely Available from IEEE
  • Inclusion Principle for Descriptor Systems

    Page(s): 3 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (513 KB) |  | HTML iconHTML  

    The purpose of this paper is to propose an expansion-contraction framework for linear constant descriptor systems within the inclusion principle for dynamic systems. Our primary objective is to provide an explicit characterization of the expansion process whereby a given descriptor system is expanded into the larger space where all its solutions are reproducible by the expanded descriptor system if appropriate initial conditions are selected. When a control law is formulated in the expanded space, the proposed characterizations provide contractibility conditions for implementation of the control law in the original system. A full freedom is provided for selecting appropriate matrices in the proposed expansion-contraction control scheme. In particular, the derived theoretical framework serves as a flexible environment for expansion-contraction control design of descriptor systems under overlapping information structure constraints. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Maximum Likelihood Estimation of State Space Models From Frequency Domain Data

    Page(s): 19 - 33
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (949 KB) |  | HTML iconHTML  

    This paper addresses the problem of estimating linear time invariant models from observed frequency domain data. Here an emphasis is placed on deriving numerically robust and efficient methods that can reliably deal with high order models over wide bandwidths. This involves a novel application of the expectation-maximization algorithm in order to find maximum likelihood estimates of state space structures. An empirical study using both simulated and real measurement data is presented to illustrate the efficacy of the solutions derived here. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Identification of Systems With Regime Switching and Unmodeled Dynamics

    Page(s): 34 - 47
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1026 KB) |  | HTML iconHTML  

    This paper is concerned with persistent identification of systems that involve deterministic unmodeled dynamics and stochastic observation disturbances, and whose unknown parameters switch values (possibly large jumps) that can be represented by a Markov chain. Two classes of problems are considered. In the first class, the switching parameters are stochastic processes modeled by irreducible and aperiodic Markov chains with transition rates sufficiently faster than adaptation rates of the identification algorithms. In this case, tracking real-time parameters by output observations becomes impossible and we show that an averaged behavior of the parameter process can be derived from the stationary measure of the Markov chain and can be estimated with periodic inputs and least-squares type algorithms. Upper and lower error bounds are established that explicitly show impact of unmodeled dynamics. In contrast, the second class of problems represents systems whose state transitions occur infrequently. An adaptive algorithm with variable step sizes is introduced for tracking the time-varying parameters. Convergence and error bounds are derived. Numerical results are presented to illustrate the performance of the algorithm. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Distributed Subgradient Methods for Multi-Agent Optimization

    Page(s): 48 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (420 KB) |  | HTML iconHTML  

    We study a distributed computation model for optimizing a sum of convex objective functions corresponding to multiple agents. For solving this (not necessarily smooth) optimization problem, we consider a subgradient method that is distributed among the agents. The method involves every agent minimizing his/her own objective function while exchanging information locally with other agents in the network over a time-varying topology. We provide convergence results and convergence rate estimates for the subgradient method. Our convergence rate results explicitly characterize the tradeoff between a desired accuracy of the generated approximate optimal solutions and the number of iterations needed to achieve the accuracy. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • On System Gains, Nonlinearity Measures, and Linear Models for Nonlinear Systems

    Page(s): 62 - 78
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (752 KB) |  | HTML iconHTML  

    This article is concerned with the assessment and derivation of (best) linear models for nonlinear systems. We introduce a general framework reminiscent of uncertainty descriptions in linear robust control theory in order to define a family of six model quality indices for linear models of nonlinear systems. Each quality index corresponds to the gain of an error system, where the nonlinear system can be represented as the interconnection of a nominal linear model and this error system. For an analysis in a certain region of operation, these gains are considered over a specified signal set. A best linear model is a linear model that minimizes the quality index and the minimal quality index serves at the same time as a measure of nonlinearity of the nonlinear system. We show that the model quality indices and nonlinearity measures can be defined under very weak assumptions, and we give conditions that guarantee the existence of optimal linear models. We discuss the structure of the problem of computing the nonlinearity measures. We show that the local linearization of a state space system is a best linear model for the limiting case of a vanishing operating range for one of the measures. We show the relation between the steady-state behavior of a system and its gain and nonlinearity measures. Furthermore we give linear models and upper bounds for nonlinearity measures for systems composed of a linear dynamic and a nonlinear static part. In the case of scalar (SISO) systems, these bounds are given by the sector bounds of the nonlinearity. Finally, it is shown that a lower bound on the nonlinearity measures can be derived using harmonic analysis. Several small examples serve to illustrate the results and the underlying ideas. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Root Locus for Random Reference Tracking in Systems With Saturating Actuators

    Page(s): 79 - 91
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1341 KB) |  | HTML iconHTML  

    This paper develops a root locus technique for random reference tracking in systems with saturating actuators. This is accomplished by introducing the notion of S-poles, which are the poles of the quasilinear system obtained by applying the method of stochastic linearization to the original system with saturation. The path traced by the S-poles on the complex plane when the gain of the controller changes from 0 to infin is the S-root locus. We show that the S-root locus is a subset of the standard root locus, which may terminate prematurely in the so-called termination points. A method for calculating these points is presented and a number of other, more subtle, differences between the usual and the S-root loci are described. In addition, the issue of amplitude truncation in terms of the S-root locus is investigated. Finally, an application of the S-root locus to hard disk drive controller design is presented. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Quantum Risk-Sensitive Estimation and Robustness

    Page(s): 92 - 107
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (779 KB) |  | HTML iconHTML  

    This paper studies a quantum risk-sensitive estimation problem and investigates robustness properties of the filter. This is a direct extension to the quantum case of analogous classical results. All investigations are based on a discrete approximation model of the quantum system under consideration. This allows us to study the problem in a simple mathematical setting. We close the paper with some examples that demonstrate the robustness of the risk-sensitive estimator. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimal Control of Multi-Stage Discrete Event Systems With Real-Time Constraints

    Page(s): 108 - 123
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (776 KB) |  | HTML iconHTML  

    We consider discrete event systems involving tasks with real-time constraints and seek to control processing times so as to minimize a cost function subject to each task meeting its own constraint. When tasks are processed over a single stage, it has been shown that there are structural properties of the optimal state trajectory that lead to very efficient solutions of such problems. When tasks are processed over multiple stages and are subject to end-to-end real-time constraints, these properties no longer hold and no obvious extensions are known. We consider such a multi-stage problem with not only stage-dependent but also task-dependent cost functions over all tasks at each stage and derive several new optimality properties. These properties lead to the idea of introducing ldquovirtualrdquo deadlines at each stage except the last one, thus partially decoupling the stages so that the known efficient solutions for single-stage problems can be used. We prove that a sequence of solutions to single-stage problems with virtual deadlines updated at each step converges to the global optimal solution of the multi-stage problem. This leads to a virtual deadline algorithm (VDA) which is scalable in the number of processed tasks. We illustrate the scalability and efficiency of the VDA through numerical examples. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Distributed Control for Identical Dynamically Coupled Systems: A Decomposition Approach

    Page(s): 124 - 135
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (640 KB) |  | HTML iconHTML  

    We consider the problem of designing distributed controllers for a class of systems which can be obtained from the interconnection of a number of identical subsystems. If the state space matrices of these systems satisfy a certain structural property, then it is possible to derive a procedure for designing a distributed controller which has the same interconnection pattern as the plant. This procedure is basically a multiobjective optimization under linear matrix inequality constraints, with system norms as performance indices. The explicit expressions for computing these controllers are given for both H infin or H 2 performance, and both for static state feedback and dynamic output feedback (in discrete time). At the end of the paper, two application examples illustrate the effectiveness of the approach. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stochastic Passivity and its Application in Adaptive Control

    Page(s): 136 - 142
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (435 KB) |  | HTML iconHTML  

    A positive-real like lemma for finite dimensional linear time invariant uncertain systems with state multiplicative noise is derived. The system uncertainties are assumed to be of either polytopic or Markov jump type. Passivity conditions for both cases are derived in terms of linear matrix inequalities. The results are used to the design a direct adaptive controller for a tracking system. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Exponential Stability of a Class of Boundary Control Systems

    Page(s): 142 - 147
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (231 KB) |  | HTML iconHTML  

    We study a class of partial differential equations (with variable coefficients) on a one dimensional spatial domain with control and observation at the boundary. For this class of systems we provide simple tools to check exponential stability. This class is general enough to include models of flexible structures, traveling waves, heat exchangers, and bioreactors among others. The result is based on the use of a generating function (the energy for physical systems) and an inequality condition at the boundary. Furthermore, based on the port Hamiltonian approach, we give a constructive method to reduce this inequality to a simple matrix inequality. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Delay-Dependent Exponential Stability of Neutral Stochastic Delay Systems

    Page(s): 147 - 152
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (222 KB) |  | HTML iconHTML  

    This technical note studies stability of neutral stochastic delay systems by linear matrix inequality approach. Delay-dependent criterion for exponential stability is presented and numerical examples are conducted to verify the effectiveness of the proposed method. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Asymptotic Optimality of Multicenter Voronoi Configurations for Random Field Estimation

    Page(s): 153 - 158
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (297 KB) |  | HTML iconHTML  

    This technical note deals with multi-agent networks performing estimation tasks. Consider a network of mobile agents with sensors that can take measurements of a spatial stochastic process. Using the kriging statistical technique, a field estimate may be calculated over the environment, with an associated error variance at each point. We study a single-snapshot scenario, in which the spatial process mean is known and each agent can only take one measurement. We consider two optimization problems with respect to the measurement locations, using as objective functions the maximum error variance and the extended prediction variance. As the correlation between distinct locations vanishes, we show that circumcenter and incenter Voronoi configurations become network configurations that optimize the maximum error variance and the extended prediction variance, respectively. We also present distributed coordination algorithms that steer the network towards these configurations. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

    Page(s): 158 - 162
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (207 KB) |  | HTML iconHTML  

    This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Feedback Stabilization Over a First Order Moving Average Gaussian Noise Channel

    Page(s): 163 - 167
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (209 KB) |  | HTML iconHTML  

    Recent developments in information theory by Y.-H. Kim have established the feedback capacity of a first order moving average additive Gaussian noise channel. Separate developments in control theory have examined linear time invariant feedback control stabilization under signal to noise ratio (SNR) constraints, including colored noise channels. This note considers the particular case of a minimum phase plant with relative degree one and a single unstable pole at z=phi (with |phi| > 1) over a first order moving average Gaussian channel. SNR constrained stabilization in this case is possible precisely when the feedback capacity of the channel satisfies CFB ges log2 |phi|. Furthermore, using the results of Kim we show that there exist linear encoding and decoding schemes that achieve stabilization within the SNR constraint precisely when CFB ges log2 |phi|. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Admissible Pole Locations for Tracking Random References

    Page(s): 168 - 171
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (382 KB) |  | HTML iconHTML  

    Admissible pole locations for tracking step inputs are well known and widely used for designing tracking controllers. In some applications, however, references are random signals rather than steps. What are admissible pole locations for tracking such references? This is the question addressed in this note. Specifically, a method for constructing admissible domains, which lead to the desired closed loop behavior, is developed and illustrated by a hard disk drive controller design. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Mapping Based Algorithm for Large-Scale Computation of Quasi-Polynomial Zeros

    Page(s): 171 - 177
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (528 KB) |  | HTML iconHTML  

    A method for computing all zeros of a retarded quasi-polynomial that are located in a large region of the complex plane is presented. The method is based on mapping the quasi-polynomial and on utilizing asymptotic properties of the chains of zeros. First, the asymptotic exponentials of the chains are determined based on the distribution diagram of the quasi-polynomial. Secondly, large regions free of zeros are defined. Finally, the zeros are located as the intersection points of the zero-level curves of the real and imaginary parts of the quasi-polynomial, which are evaluated over the areas of the region outside those free of zeros. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Simplified Design for Strict Lyapunov Functions Under Matrosov Conditions

    Page(s): 177 - 183
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (428 KB) |  | HTML iconHTML  

    We construct strict Lyapunov functions for broad classes of nonlinear systems satisfying Matrosov type conditions. Our new constructions are simpler than the designs available in the literature. We illustrate the practical interest of our designs using a globally asymptotically stable biological model. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimization of PID Controller Based on Maximization of the Proportional Gain Under Constraints on Robustness and Sensitivity to Measurement Noise

    Page(s): 184 - 189
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (852 KB) |  | HTML iconHTML  

    This technical note presents a new, simple and effective, four-parameters proportional-integral-derivative (PID) optimization method. The set of adjustable parameters is defined by the proportional gain k, integral gain ki, damping ratio of the controller zeros (DRCZ), and desired value of the sensitivity to measurement noise Mn. Given Mn and desired value of the maximum sensitivity Ms, for both maximization of k and maximization of ki, only three nonlinear algebraic equations need to be solved for a few values of DRCZ. Contrary to the method based on maximization of ki, in the method based on maximization of k the improvement of performance is obtained by decreasing DRCZ from 1 to the value corresponding to the minimum of the integrated absolute error (IAE). Moreover, this is achieved without deteriorating robustness to the model uncertainties, for a large class of stable processes. Compared to the recently proposed PID optimization methods, for the same Ms and Mn, lower values of IAE and M p are obtained by using the method presented here. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Access over 1 million articles - The IEEE Digital Library [advertisement]

    Page(s): 190
    Save to Project icon | Request Permissions | PDF file iconPDF (370 KB)  
    Freely Available from IEEE
  • IEEE copyright form

    Page(s): 191 - 192
    Save to Project icon | Request Permissions | PDF file iconPDF (1065 KB)  
    Freely Available from IEEE
  • IEEE Control Systems Society Information

    Page(s): C3
    Save to Project icon | Request Permissions | PDF file iconPDF (42 KB)  
    Freely Available from IEEE

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