DocumentCode :
1098555
Title :
Adaptive robust extended Kalman filter for nonlinear stochastic systems
Author :
Xiong, K. ; Zhang, H. ; Liu, L.
Author_Institution :
Nat. Lab. of Space Intell. Control, Beijing Inst. of Control Eng., Beijing
Volume :
2
Issue :
3
fYear :
2008
fDate :
3/1/2008 12:00:00 AM
Firstpage :
239
Lastpage :
250
Abstract :
The authors analyse the error behaviour of the robust extended Kalman filter (REKF) for nonlinear stochastic systems. On the basis of some standard results about the boundedness of stochastic processes, it is specified that stability of the REKF cannot be guaranteed. In order to solve this problem, a novel method is proposed to design the REKF so that the sufficient conditions to ensure filter stability will be fulfilled. Furthermore, an adaptive scheme is adopted to automatically tune the error covariance matrix in response to the changing environment. Numerical example shows the superiority of the proposed adaptive REKF over the usual extended Kalman filter (EKF), the REKF and the adaptive EKF.
Keywords :
Kalman filters; adaptive control; covariance matrices; filtering theory; nonlinear control systems; nonlinear filters; robust control; stochastic systems; adaptive robust extended Kalman filter; error covariance matrix; filter stability; nonlinear stochastic systems; stochastic processes;
fLanguage :
English
Journal_Title :
Control Theory & Applications, IET
Publisher :
iet
ISSN :
1751-8644
Type :
jour
DOI :
10.1049/iet-cta:20070096
Filename :
4470552
Link To Document :
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