Wiener State Estimator for Non-regular Descriptor System

Abstract

Using the modern time-series analysis method in the time domain, based on the autoregressive moving average (ARMA) innovation model and white noise estimator, non-regular descriptor discrete-time stochastic linear systems are researched. Under assumption 1~3, an asymptotically stable reduced-order Wiener state estimator for descriptor systems is given by using projection and block matrix theories. Non-regular descriptor systems include general descriptor systems in them. And the algorithm is reduced-order. It avoids the solution of the Riccati equations and Diophantine equations. So that it reduces the computational burden, and is suitable for real time applications.