Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution AlgorithmOACSTPCDEI

This article mainly investigates the fuzzy optimiza-tion robust control issue for nonlinear networked systems charac-terized by the interval type-2(IT2)fuzzy technique under a dif-ferential evolution algorithm.To provide a more reasonable uti-lization of the constrained communication channel,a novel adap-tive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conser-vative design of the fuzzy imperfect premise matching(IPM)con-troller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the dif-ferential evolution algorithm is first provided for IT2 Takagi-Sugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simu-lation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer com-munication resources.