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Topics in Stochastic Systems: Modelling, Estimation and Adaptive Control

  • Book
  • © 1991

Overview

Editors:
  1. L. Gerencséer
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  2. P. E. Caines
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Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 161)

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Table of contents (16 chapters)

  1. Front Matter

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  2. Direct modeling of white noise in stochastic systems

    • Arunabha Bagchi, Ravi Mazumdar
    Pages 1-30

  3. Markovian representations of cyclostationary processes

    • Sergio Bittanti, Giuseppe De Nicolao
    Pages 31-46

  4. Parametriztions of linear stochastic systems

    • Bokor J., L. Keviczky
    Pages 47-65

  5. Stochastic realization for approximate modeling

    • Andrea Gombani
    Pages 66-78

  6. Representation of inner products and stochastic realization

    • Gy. Michaletzky, G. Tusnády
    Pages 79-102

  7. On realization and identification of stochastic bilinear systems

    • György Terdik
    Pages 103-115

  8. On stochastic partial differential equations. Results on approximations

    • István Gyöngy
    Pages 116-136

  9. Developments in parameter bounding

    • John P. Norton, Sándor M. Veres
    Pages 137-158

  10. Recent progress in parallel stochastic approximations

    • G. Yin
    Pages 159-184

  11. On the adaptive stabilization and ergodic behaviour of stochastic systems with jump-Markov parameters via nonlinear filtering

    • Peter E. Caines, Karim Nassiri-Toussi
    Pages 185-215

  12. Identification and adaptive control for ARMAX systems

    • Han-Fu Chen, Lei Guo, Ji-Feng Zhang
    Pages 216-241

  13. Some methods for the adaptive control of continuous time linear stochastic systems

    • T. E. Duncan, B. Pasik-Duncan
    Pages 242-267

  14. Strong approximation results in estimation and adaptive control

    • LászlĂł GerencsĂ©r
    Pages 268-299

  15. Stochastic adaptive control: Results and perspective

    • G. C. Goodwin, M. Gevers, D. Q. Mayne, V. Wertz
    Pages 300-334

  16. Information bounds, certainty equivalence and learning in asymptotically efficient adaptive control of time-invariant stochastic systems

    • Tze Leung Lai
    Pages 335-368

  17. Stability of Markov chains on topological spaces with applications to adaptive control and time series analysis

    • Sean P. Meyn
    Pages 369-401
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Keywords

About this book

This book contains a collection of survey papers in the areas of modelling, estimation and adaptive control of stochastic systems describing recent efforts to develop a systematic and elegant theory of identification and adaptive control. It is meant to provide a fast introduction to some of the recent achievements. The book is intended for graduate students and researchers interested in statistical problems of control in general. Students in robotics and communication will also find it valuable. Readers are expected to be familiar with the fundamentals of probability theory and stochastic processes.

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