Abstract   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, for the one-step prediction, 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 parameter-dependent Lyapunov function.
['Carlos E. de Souza', 'Minyue Fu', 'Karina A. Barbosa']
ROBUST FILTERING FOR UNCERTAIN LINEAR DISCRETE-TIME DESCRIPTOR SYSTEMS