Control and Dynamic Systems V26 - 1st Edition - ISBN: 9780120127269, 9780323154659

Control and Dynamic Systems V26

1st Edition

Advances in Theory and Applications

Editors: C.T. Leonides
eBook ISBN: 9780323154659
Imprint: Academic Press
Published Date: 23rd November 1987
Page Count: 352
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Control and Dynamic Systems: Advances in Theory and Application, Volume 26: System Identification and Adaptive Control, Part 2 of 3 deals with system parameter identification and adaptive control. It presents useful techniques for effective stochastic adaptive control systems. This volume presents a powerful technique for identifying discrete time and continuous time linear time-invariant multivariable systems. It also includes the use of identifiable representations for linear multivariable systems; parametric identification of transfer functions of linear system; compares model reference adaptive control and model identification control; estimation of transfer function models; multivariable self-tuning control; and covariance analysis. This volume ends with powerful techniques for adaptive control for stochastic linear systems.
This text is of great value to practitioners in the field who want a comprehensive reference source of techniques with significant applied implications.

Table of Contents

Contents Preface Techniques for Identification of Linear Time-Invariant Multivariable Systems I. Introduction II. Preliminary III. Row Searching and the Echelon-Form Solution IV. Persistent Excitation of Input Sequences V. Identification of Discrete-Time Systems VI. Identification of Continuous-Time Systems VI. Noisy Measurements References Techniques for the Selection of Identifiable Parametrizations for Multivariable Linear Systems I. Introduction II. Models III. Identifiability IV. The Structure of S(n) V. Canonical and Pseudocanonical Forms VI. Other Identifiable Parametrizations VII. The Estimation of the Structure VIII. Conclusions References Parametric Methods for Identification of Transfer Functions of Linear Systems I. Introduction II. Measures of Model Quality III. Prediction Error Identification Methods IV. Asymptotic Properties of the Estimated Transfer Functions V. Minimizing the Bias Contribution VI. Minimizing the Variance Contribution VII. Minimizing the Design Criteria References Techniques in Dynamics Systems Parameter-Adaptive Control I. Introduction II. Approaches to Parameter-Adaptive Control III. Parameter Estimation IV. Control Algorithm Design V. Combinations VI. Convergence Conditions VII. Steps for the Application VIII. Supervision and Coordination IX. Implementation on Microcomputers X. Applications XI. Conclusions References Estimation of Transfer Function Models Using Mixed Recursive and Nonrecursive Methods I. Introduction II. Overview of Past Work III. The New Algorithm IV. Examples V. Summary VI. Appendix References Techniques for Multivariable Self-Tuning Control I. Introduction II. Self-Tuning Control of Stochastic Systems III. Explicit LOG Self-Tu


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© Academic Press 1987
Academic Press
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C.T. Leonides

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