Adaptive event‐triggered quantized H∞ fuzzy filtering for T‐S fuzzy systems via fuzzy Lyapunov–Krasovskii functional method

Summary This article is concerned on the problem of adaptive event‐triggered quantized fuzzy filtering for networked T‐S fuzzy control systems under imperfect premise matching. First, a novel adaptive event‐triggered communication scheme for networked fuzzy control systems is built to save more limited network bandwidth, where the event‐triggered parameter is changed with the output fluctuation. Second, a fuzzy filter with the imperfect premise matching is designed. Under consideration of event‐triggered scheme and quantization method, an unified filtering error model is well constructed, which contains time delay and parameter uncertainties. Then, a new augmented fuzzy Lyapunov–Krasovskii functional including a fuzzy Lyapunov matrix and a delay product term is established, and sufficient conditions are derived to guarantee the asymptotic stability of the filtering error system with a given performance. Moreover, the corresponding filter can be designed by solving a set of linear matrix inequalities. Finally, a numerical example is put forward to illustrate the effectiveness and advantages of the proposed method.