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.
Original languageEnglish
Pages (from-to)480-487
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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