Journal of University of Chinese Academy of Sciences >
Adaptive Observer Design for Bounded Dynamic Stochastic Systems
Received date: 2004-06-23
Revised date: 2004-08-06
Online published: 2005-07-15
Supported by
supported by the National Natural Science Foundation of China(60128303)
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.
Key words： observer; adaptive updat ing rule; residual signal; B-spline model
SHEN Ling , WANG Hong , YUE Hong . Adaptive Observer Design for Bounded Dynamic Stochastic Systems[J]. Journal of University of Chinese Academy of Sciences, 2005 , 22(4) : 478 -487 . DOI: 10.7523/j.issn.2095-6134.2005.4.013
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