Robust Kalman filter design for hybrid systems with norm-bounded unknown nonlinearities

Author

Shi, Peng ; Karan, Mehmet ; Kaya, Yalcin

Author_Institution

Sch. of Math., Univ. of South Austrlia, Salisbury, SA, Australia

Volume

2

fYear

2000

fDate

2000

Firstpage

1597

Abstract

Considers the filtering problem for a class of linear hybrid systems with nonlinear uncertainties and Markovian jump parameters. The unknown nonlinearities in the system are time-varying and norm-bounded. First, we show the equivalence of the norm bounded linear and nonlinear uncertainty sets. 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

Keywords

Kalman filters; Markov processes; Riccati equations; filtering theory; linear systems; nonlinear systems; state estimation; time-varying systems; uncertain systems; Markovian jump parameters; coupled Riccati-like equations; estimation error; filtering problem; hybrid systems; linear uncertainties; nonlinear uncertainties; norm-bounded unknown nonlinearities; robust Kalman filter; Estimation error; Filtering; Linear systems; Nonlinear equations; Nonlinear filters; Riccati equations; Robustness; Time varying systems; Uncertainty; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2000. Proceedings of the 39th IEEE Conference on

Conference_Location

Sydney, NSW

ISSN

0191-2216

Print_ISBN

0-7803-6638-7

Type

conf

DOI

10.1109/CDC.2000.912088

Filename

912088