The UIO-based LMMSE filter for NCSs with packet dropout

Abstract

This paper puts forward a UIO-based linear-minimum-mean-square-error (LMMSE) estimation problem of a class of the net-worked control systems (NCSs), and the disturbance of the state and its measurements is zero mean white noise with covariance being ; An unknown input observer (UIO) is established stemmed from a linear multi-sensor model and a linear time-varying estimation error system is proposed where packet dropouts are presented as zero-mean white input noise. Based on the error system, a LMMSE estimator is set up to obtain an error estimate of the state. By compensating the primary estimate of the UIO with the error estimate of the LMMSE, a much more accurate estimate of the state is achieved. A numerical example of distributive target tracking is given to illustrate the proposed estimator.