Optimal Linear Filtering for Networked Control Systems with Random Matrices, Correlated Noises, and Packet Dropouts

Abstract

In this paper, the optimal linear filtering problem for linear discrete-time stochastic systems with random matrices, correlated noises and packet dropouts is studied where the random matrices are real and appear both in the the state and measurement equations. Using an equivalent transformation for random matrices and some results presented in this paper, an optimal linear filter for the system under consideration is developed. The developed optimal filter has a recursive pattern, and its computational complexity does not change with time. Number examples with simulation results are given to examine the performance of the developed optimal linear filter.