Nonfragile peak-to-peak filtering for discrete-time Takagi-Sugeno fuzzy systems with dynamic quantizations

Abstract

This paper investigates the problem of nonfragile peak-to-peak filtering for a class of discrete-time nonlinear networked control systems with dynamic quantizations. The Takagi-Sugeno fuzzy model is applied to approximate the considered nonlinear networked control systems. The perturbations are also considered in the peak-to-peak filter to be designed. Unlike most work about the peak-to-peak filtering for dynamic systems with quantization, both the performance output signal and measurement output signal are quantized by two different dynamic quantizers in our work. The main attention is to design the nonfragile peak-to-peak filter which guarantees the filtering error system to be asymptotically stable and possess a peak-to-peak performance index. By employing the fuzzy basis-dependent Lyapunov function approach and the S-procedure, new sufficient conditions about designing the nonfragile peak-to-peak filter have been established, which are expressed in the form of linear matrix inequalities. In the end, a numerical example is offered to verify the effectiveness of the designed nonfragile peak-to-peak filter.