Robust filtering for uncertain linear discrete-time descriptor systems

This paper is concerned with the problem of robust filtering for uncertain linear discrete-time descriptor systems. The matrices of the system state-space model are uncertain and supposed to belong to a given polytope. A linear matrix inequality based method is proposed for designing linear stationary strictly proper filters that guarantee the asymptotic stability of the estimation error and an optimized upper-bound on the asymptotic error variance, irrespective of the parameter uncertainty. The proposed robust filter design is based on a parameterdependent Lyapunov function.