DocumentCode :
2186697
Title :
Adaptive observer with exponential forgetting factor for linear time varying systems
Author :
Zhang, Qinghua ; Clavel, Arnaud
Author_Institution :
IRISA-INRIA, Rennes, France
Volume :
4
fYear :
2001
fDate :
2001
Firstpage :
3886
Abstract :
For the purpose of recursive joint estimation of state and parameters in continuous-time state space systems, the algorithm proposed in this paper improves the consistency of an adaptive observer for multi-input-multi-output (MIMO) linear time varying (LTV) systems. The new algorithm makes use of a time varying gain matrix for parameter estimation, instead of the constant gain matrix used by the previously reported algorithm. It is exponentially stable, converges in the mean for both state and parameter estimations. The covariance matrix of the parameter estimation error can be made arbitrarily small by choosing a sufficiently small forgetting factor
Keywords :
MIMO systems; asymptotic stability; continuous time systems; covariance matrices; linear systems; observers; recursive estimation; time-varying systems; MIMO linear time varying systems; adaptive observer; covariance matrix; exponential forgetting factor; exponential stability; multi-input-multi-output system; parameter estimation; recursive joint estimation; state estimation; time varying gain matrix; Convergence; Covariance matrix; Least squares approximation; MIMO; Observers; Parameter estimation; Resonance light scattering; State estimation; State-space methods; Time varying systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-7061-9
Type :
conf
DOI :
10.1109/.2001.980478
Filename :
980478
Link To Document :
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