Optimal State Estimation for Discrete-Time Markov Jump Systems with Missing Observations

Abstract EN

This paper is concerned with the optimal linear estimation for a class of direct-time Markov jump systems with missing observations.

An observer-based approach of fault detection and isolation (FDI) is investigated as a detection mechanic of fault case.

For systems with known information, a conditional prediction of observations is applied and fault observations are replaced and isolated; then, an FDI linear minimum mean square error estimation (LMMSE) can be developed by comprehensive utilizing of the correct information offered by systems.

A recursive equation of filtering based on the geometric arguments can be obtained.

Meanwhile, a stability of the state estimator will be guaranteed under appropriate assumption.