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Guaranteed performance robust Kalman filter for continuous-time Markovian jump nonlinear system with uncertain noise

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journal contribution
posted on 06.12.2017, 00:00 by J Zhu, J Park, KS Lee, Maksym Spiryagin
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 arc 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.

Funding

Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)

History

Issue

2008

Start Page

1

End Page

12

Number of Pages

12

eISSN

1563-5147

ISSN

1024-123X

Location

United States

Publisher

Hindawi Publishing Corporation

Language

en-aus

Peer Reviewed

Yes

Open Access

No

Era Eligible

Yes

Journal

Mathematical problems in engineering.