Title :
Kalman filtering for continuous-time uncertain systems with Markovian jumping parameters
Author :
Shi, Peng ; Boukas, El-Kebir ; Agarwal, Ramesh K.
Author_Institution :
Sch. of Math., Univ. of South Australia, Mawson Lakes, SA, Australia
fDate :
8/1/1999 12:00:00 AM
Abstract :
Studies the problem of Kalman filtering for a class of uncertain linear continuous-time systems with Markovian jumping parameters. The system under consideration is subjected to time-varying norm-bounded parameter uncertainties in the state and measurement equations. Stochastic quadratic stability of the above system is analyzed. A state estimator is designed such that the covariance of the estimation error is guaranteed to be within a certain bound for all admissible uncertainties, which is in terms of solutions of two sets of coupled algebraic Riccati equations
Keywords :
Kalman filters; Markov processes; Riccati equations; continuous time systems; covariance matrices; filtering theory; linear systems; stability; state estimation; time-varying systems; uncertain systems; Kalman filtering; Markovian jumping parameters; Stochastic quadratic stability; continuous-time uncertain systems; coupled algebraic Riccati equations; time-varying norm-bounded parameter uncertainties; Estimation error; Filtering; Kalman filters; Nonlinear filters; Riccati equations; Stability analysis; State estimation; Stochastic systems; Time varying systems; Uncertain systems;
Journal_Title :
Automatic Control, IEEE Transactions on
