Relaxed Peak-to-Peak Filtering Design for Networked Nonlinear DC Motor Systems with Quantization

This paper deals with the matter of relaxed peak-to-peak filtering for nonlinear networked DC motor with quantization. The powerful Takagi-Sugeno (T-S) fuzzy model is used to model the nonlinear terms. With the help of proposing a so-called switching filter, more filter gain matrices can be introduced and the derived result is less than the one with single matrix given in the recent literature. Further, some free additional matrices are also introduced for obtaining feasible solution to the underlying filter gain matrices in terms of linear matrix inequality. At last, the validity of the given means is demonstrated by a simulation instance.