Robust Kalman Filter Design for Markovian Jump Linear Systems with Norm-Bounded Unknown Nonlinearities

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Shi, Peng, Karan, Mehmet and Kaya, Yalcin (2005) Robust Kalman Filter Design for Markovian Jump Linear Systems with Norm-Bounded Unknown Nonlinearities. Circuits Systems and Signal Processing, 24 (2). pp. 135-150. ISSN 0278-081X

Abstract

This paper considers the problems of stability and filtering for a class of linear hybrid systems with nonlinear uncertainties and Markovian jump parameters. The hybrid system under study involves a continuous-valued system state vector and a discretevalued system mode. The unknown nonlinearities in the system are time varying and norm bounded. The Markovian jump parameters are modeled by a Markov process with a finite number of states. First, we show the equivalence of the sets of norm-bounded linear and nonlinear uncertainties. Then, instead of the original hybrid linear system with nonlinear uncertainties, we consider the same system with linear uncertainties. By using a Riccati equation approach for this new system, a robust filter is designed using two sets of coupled Riccati-like equations such that the estimation error is guaranteed to have an upper bound.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/4581
DOI https://doi.org/10.1007/s00034-004-0702-2
Official URL http://dx.doi.org/10.1007/s00034-004-0702-2
Subjects Current > FOR Classification > 0906 Electrical and Electronic Engineering
Current > FOR Classification > 0102 Applied Mathematics
Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
Keywords ResPubID18843, Kalman filters , Markov processes , Riccati equations , robust filter, linear systems, nonlinear systems
Citations in Scopus 49 - View on Scopus
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