Generalized System Of Price Cuts Kalman And Wiener State Estimators

Based on three canonical forms of descriptor stochastic systems, applying the Kalman filtering and white noise estimation theory, the three reduced-order Kalman state estimators and Wiener state estimators of descriptor systems are presented respectively. They can handle the prediction ,filtering and smoothing problems in a unified framework, and have the symptotic stability. Otherwise, the three reduced-order pole-assignment fixed-lag Kalmam smoothers having a global asymptotic stability are presented. Compared with non-reduced-order estimators, they can obviously reduce the computational burden, and is suitable for real time appplycations. Many simulation examples show effectiveness of the proposed algorithms.