Event-based asynchronous dissipative filtering for fuzzy nonhomogeneous Markov switching systems with variable packet dropouts
Xia Zhou, Jun Cheng, Jinde Cao, Ju H. Park
Abstract
This work concerns the event-based asynchronous filtering problem for T-S fuzzy nonhomogeneous Markov switching systems with variable packet dropouts. The discrete-time nonhomogeneous Markov process is adopted to depict mode switching among subsystems, in which the time-varying transition probabilities are characterized by a polytope structure. The variable packet dropouts are developed to describe the randomly occurring packet dropouts, where the arriving rate remains variable and uncertain. Aiming to save the limited network bandwidth, event-triggered strategy and quantization scheme are presented. By establishing the fuzzy-rule-dependent Lyapunov functional and applying a hidden Markov model policy, sufficient criteria are gained and asynchronous filters are designed by solving linear matrix inequalities (LMIs). Finally, the applicability of the proposed filtering strategy is verified by an inverted pendulum model.