Identification and Stochastic Adaptive Control

  • Han-Fu Chen
  • Lei Guo

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

Table of contents

  1. Front Matter
    Pages i-xi
  2. Chen Han-Fu, Lei Guo
    Pages 1-23
  3. Chen Han-Fu, Lei Guo
    Pages 25-50
  4. Chen Han-Fu, Lei Guo
    Pages 51-87
  5. Chen Han-Fu, Lei Guo
    Pages 89-151
  6. Chen Han-Fu, Lei Guo
    Pages 153-186
  7. Chen Han-Fu, Lei Guo
    Pages 187-215
  8. Chen Han-Fu, Lei Guo
    Pages 217-241
  9. Chen Han-Fu, Lei Guo
    Pages 293-331
  10. Chen Han-Fu, Lei Guo
    Pages 333-373
  11. Chen Han-Fu, Lei Guo
    Pages 375-401
  12. Chen Han-Fu, Lei Guo
    Pages 403-419
  13. Back Matter
    Pages 421-435

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.


Martingal Martingale Martingale difference sequence Parameter approximation calculus control control system evolution probability theory science stochastic differential equation stochastic systems

Authors and affiliations

  • Han-Fu Chen
    • 1
  • Lei Guo
    • 1
  1. 1.Institute of Systems Science, Academia SinicaPeking UniversityBeijingChina

Bibliographic information

  • DOI
  • Copyright Information Birkhäuser Boston 1991
  • Publisher Name Birkhäuser, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-6756-0
  • Online ISBN 978-1-4612-0429-9
  • Series Print ISSN 2324-9749
  • Buy this book on publisher's site