Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise

Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise

Robust Kalman filtering design for continuous-time Markovian jump nonlinear systems with uncertain noise was investigated. Because of complexity of Markovian jump systems, the statistical characteristics of system noise and observation noise are time-varying or unmeasurable inste...

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Main Authors: Jin Zhu, Junhong Park, Kwan-Soo Lee, Maksym Spiryagin
Format: Article
Language:English
Published: Hindawi Limited 2008-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2008/583947
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spelling doaj-377ce446c86e430eb0de75ed780fb8552020-11-25T01:08:01ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472008-01-01200810.1155/2008/583947583947Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain NoiseJin Zhu0Junhong Park1Kwan-Soo Lee2Maksym Spiryagin3Department of Mechanical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South KoreaDepartment of Mechanical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South KoreaDepartment of Mechanical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South KoreaDepartment of Mechanical Engineering, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South KoreaRobust Kalman filtering design for continuous-time Markovian jump nonlinear systems with uncertain noise was investigated. Because of complexity of Markovian jump systems, the statistical characteristics of system noise and observation noise are time-varying or unmeasurable instead of being stationary. In view of robust estimation, maximum admissible upper bound of the uncertainty to noise covariance matrix was given based on system state estimation performance. As long as the noise uncertainty is limited within this bound via noise control, the Kalman filter has robustness against noise uncertainty, and stability of dynamic systems can be ensured. It is proved by game theory that this design is a robust mini-max filter. A numerical example shows the validity of this design.http://dx.doi.org/10.1155/2008/583947
collection DOAJ
language English
format Article
sources DOAJ
author Jin Zhu
Junhong Park
Kwan-Soo Lee
Maksym Spiryagin
spellingShingle Jin Zhu
Junhong Park
Kwan-Soo Lee
Maksym Spiryagin
Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise
Mathematical Problems in Engineering
author_facet Jin Zhu
Junhong Park
Kwan-Soo Lee
Maksym Spiryagin
author_sort Jin Zhu
title Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise
title_short Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise
title_full Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise
title_fullStr Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise
title_full_unstemmed Guaranteed Performance Robust Kalman Filter for Continuous-Time Markovian Jump Nonlinear System with Uncertain Noise
title_sort guaranteed performance robust kalman filter for continuous-time markovian jump nonlinear system with uncertain noise
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2008-01-01
description Robust Kalman filtering design for continuous-time Markovian jump nonlinear systems with uncertain noise was investigated. Because of complexity of Markovian jump systems, the statistical characteristics of system noise and observation noise are time-varying or unmeasurable instead of being stationary. In view of robust estimation, maximum admissible upper bound of the uncertainty to noise covariance matrix was given based on system state estimation performance. As long as the noise uncertainty is limited within this bound via noise control, the Kalman filter has robustness against noise uncertainty, and stability of dynamic systems can be ensured. It is proved by game theory that this design is a robust mini-max filter. A numerical example shows the validity of this design.
url http://dx.doi.org/10.1155/2008/583947
work_keys_str_mv AT jinzhu guaranteedperformancerobustkalmanfilterforcontinuoustimemarkovianjumpnonlinearsystemwithuncertainnoise
AT junhongpark guaranteedperformancerobustkalmanfilterforcontinuoustimemarkovianjumpnonlinearsystemwithuncertainnoise
AT kwansoolee guaranteedperformancerobustkalmanfilterforcontinuoustimemarkovianjumpnonlinearsystemwithuncertainnoise
AT maksymspiryagin guaranteedperformancerobustkalmanfilterforcontinuoustimemarkovianjumpnonlinearsystemwithuncertainnoise
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