State Estimation for Markov Jump Systems with Nonlinearity and observation delay*

This paper is concerned with the state estimation of discrete-time nonlinear Markov jump systems with observation delays. By introducing a set of equivalent delay-free observations and defining a reorganized Markov chain, the estimation of delayed nonlinear systems is reduced to the one of delay-free Markov jump nonlinear systems. A minimum mean square error estimator is designed by minimizing the upper bound of the estimation error covariance matrix, where the upper bound of the error covariance matrix is determined by a set of auxiliary constant parameters. The filter gains are given in terms of a set of generalized coupled difference Riccati equations.