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Identification and Stochastic Adaptive Control

  • Book
  • © 1991

Overview

Authors:
  1. Han-Fu Chen

    1. Institute of Systems Science, Academia Sinica, Peking University, Beijing, China

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  2. Lei Guo

    1. Institute of Systems Science, Academia Sinica, Peking University, Beijing, China

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: Systems & Control: Foundations & Applications (SCFA)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xi
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  2. Probability Theory Preliminaries

    • Chen Han-Fu, Lei Guo
    Pages 1-23

  3. Limit Theorems on Martingales

    • Chen Han-Fu, Lei Guo
    Pages 25-50

  4. Filtering and Control for Linear Systems

    • Chen Han-Fu, Lei Guo
    Pages 51-87

  5. Coefficient Estimation for ARMAX Models

    • Chen Han-Fu, Lei Guo
    Pages 89-151

  6. Stochastic Adaptive Tracking

    • Chen Han-Fu, Lei Guo
    Pages 153-186

  7. Coefficient Estimation in Adaptive Control Systems

    • Chen Han-Fu, Lei Guo
    Pages 187-215

  8. Order Estimation

    • Chen Han-Fu, Lei Guo
    Pages 217-241

  9. Optimal Adaptive Control with Consistent Parameter Estimate

    • Chen Han-Fu, Lei Guo
    Pages 243-291

  10. ARX(∞) Model Approximation

    • Chen Han-Fu, Lei Guo
    Pages 293-331

  11. Estimation for Time-Varying Parameters

    • Chen Han-Fu, Lei Guo
    Pages 333-373

  12. Adaptive Control of Time-Varying Stochastic Systems

    • Chen Han-Fu, Lei Guo
    Pages 375-401

  13. Continuous-Time Stochastic Systems

    • Chen Han-Fu, Lei Guo
    Pages 403-419

  14. Back Matter

    Pages 421-435
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Keywords

About this book

Identifying the input-output relationship of a system or discovering the evolutionary law of a signal on the basis of observation data, and applying the constructed mathematical model to predicting, controlling or extracting other useful information constitute a problem that has been drawing a lot of attention from engineering and gaining more and more importance in econo­ metrics, biology, environmental science and other related areas. Over the last 30-odd years, research on this problem has rapidly developed in various areas under different terms, such as time series analysis, signal processing and system identification. Since the randomness almost always exists in real systems and in observation data, and since the random process is sometimes used to model the uncertainty in systems, it is reasonable to consider the object as a stochastic system. In some applications identification can be carried out off line, but in other cases this is impossible, for example, when the structure or the parameter of the system depends on the sample, or when the system is time-varying. In these cases we have to identify the system on line and to adjust the control in accordance with the model which is supposed to be approaching the true system during the process of identification. This is why there has been an increasing interest in identification and adaptive control for stochastic systems from both theorists and practitioners.

Authors and Affiliations

  • Institute of Systems Science, Academia Sinica, Peking University, Beijing, China

    Han-Fu Chen, Lei Guo

Bibliographic Information

  • Book Title: Identification and Stochastic Adaptive Control

  • Authors: Han-Fu Chen, Lei Guo

  • Series Title: Systems & Control: Foundations & Applications

  • DOI: https://doi.org/10.1007/978-1-4612-0429-9

  • Publisher: Birkhäuser Boston, MA

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 1991

  • Hardcover ISBN: 978-0-8176-3597-8Published: 01 November 1991

  • Softcover ISBN: 978-1-4612-6756-0Published: 06 October 2012

  • eBook ISBN: 978-1-4612-0429-9Published: 06 December 2012

  • Series ISSN: 2324-9749

  • Series E-ISSN: 2324-9757

  • Edition Number: 1

  • Number of Pages: XI, 435

  • Topics: Science, Humanities and Social Sciences, multidisciplinary

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