Distributed fusion robust filter for multisensor networked singular control system with uncertain variances and missing measurement

Abstract

A distributed fusion time‐varying robust filtering algorithm for multisensor networked singular control system is studied in this paper, mainly aiming at the system with missing measurement and uncertain variances in practical application. First, the singular value decomposition (SVD) method and de‐randomization method are used to transform the singular control system into a standard system only with uncertain variances. Based on the new standard system, a minimax robust local Kalman filter is proposed by using the minimax robust estimation principle, which ensures that the actual filtering error variance has the corresponding minimum upper bound for all allowable uncertainties. Further, the robust local and distributed fusion filters for original singular control systems are proposed, and the actual and conservative filtering error variances are obtained. Their robustness is proved by Lyapunov equation method and nonnegative definite matrix decomposition method. A simulation example of two‐loop system verifies the effectiveness of the proposed results.