State Estimation for Non-linear Sampled-Data Descriptor Systems: A Robust Extended Kalman Filtering Approach

Abstract

This paper proposes a state estimation method for a class of norm-bounded non-linear sampled-data descriptor systems using the Kalman filtering method. The descriptor model is firstly discretized to obtain a discrete-time non-singular one. Then a model of robust extended Kalman filter is proposed for the state estimation based on the discretized non-linear non-singular system. As parameters are introduced in for transforming descriptor systems into non-singular ones, there exist uncertainties in the state of the systems. To solve this problem, an optimized upper-bound is proposed so that the convergence of the estimation error co-variance matrix is guaranteed in the paper. A simulating example is proposed to verify the validity of this method at last.