A novel unbiased [formula omitted] filter design for 2-D Markov jump systems in the Roesser model with general transition probabilities

Abstract

The paper delves into the intricate details of unbiased H∞ filtering for 2-D Markov jump systems with general transition probabilities in the light of the Roesser model. In order to allow the Markov jump systems to better model practical engineering applications, general transition probabilities are introduced. These probabilities are more flexible, encompassing all unknown, all known, and partially unknown cases to improve their practical applicability. The goal of this study is to showcase a novel unbiased filter to make the filtering error system mean-square asymptotically stable and meet a specified H∞ disturbance attenuation performance. By constructing the Lyapunov function, sufficient condition for the corresponding filter to exist and the solutions of its parameters are given through linear matrix inequalities. Eventually, the Darboux equation is used to prove the utility of the presented filter.