Adaptive observer design for bounded dynamic stochastic systems

L. Shen, H. Wang, H. Yue

Research output: Contribution to journalArticle

Abstract

This paper considers the state observation problem for bounded dynamic stochastic systems by using B-spline model to approximate output probability density functions. First, a form of residual signal is considered for the output probability density function using square root B-spline neural network model,and the on-line tuning of the observer gain is obtained using Lyapunov analysis. Then a new logarithm B-spline model is presented and the adaptive observer is designed. Finally, two simulated examples are used to demonstrate the proposed algorithms, and desired results have been obtained.
LanguageEnglish
Pages480-487
Number of pages8
JournalJournal of the Graduate School of the Chinese Academy of Sciences
Volume22
Issue number4
Publication statusPublished - 2005

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Stochastic systems
Splines
Probability density function
Tuning
Neural networks

Keywords

  • observer
  • adaptive updating rule
  • residual signal
  • B-spline model

Cite this

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Adaptive observer design for bounded dynamic stochastic systems. / Shen, L.; Wang, H.; Yue, H.

In: Journal of the Graduate School of the Chinese Academy of Sciences, Vol. 22, No. 4, 2005, p. 480-487.

Research output: Contribution to journalArticle

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