Anti-windup compensation design for a class of distributed time-delayed cellular neural networks  

作　　者：HE Hanlin ZHAMiao BIAN Shaofeng 

机构地区：[1]Department of Basic Courses,Naval University of Engineering,Wuhan 430033,China [2]Department of Navigation Engineering,Naval University of Engineering,Wuhan 430033,China

出　　处：《Journal of Systems Engineering and Electronics》2019年第6期1212-1223,共12页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(61374003; 41631072);the Academic Foundation of Naval University of Engineering(20161475)

摘　　要：Both time-delays and anti-windup(AW)problems are conventional problems in system design,which are scarcely discussed in cellular neural networks(CNNs).This paper discusses stabilization for a class of distributed time-delayed CNNs with input saturation.Based on the Lyapunov theory and the Schur complement principle,a bilinear matrix inequality(BMI)criterion is designed to stabilize the system with input saturation.By matrix congruent transformation,the BMI control criterion can be changed into linear matrix inequality(LMI)criterion,then it can be easily solved by the computer.It is a one-step AW strategy that the feedback compensator and the AW compensator can be determined simultaneously.The attraction domain and its optimization are also discussed.The structure of CNNs with both constant timedelays and distribute time-delays is more general.This method is simple and systematic,allowing dealing with a large class of such systems whose excitation satisfies the Lipschitz condition.The simulation results verify the effectiveness and feasibility of the proposed method.Both time-delays and anti-windup(AW) problems are conventional problems in system design, which are scarcely discussed in cellular neural networks(CNNs). This paper discusses stabilization for a class of distributed time-delayed CNNs with input saturation. Based on the Lyapunov theory and the Schur complement principle, a bilinear matrix inequality(BMI) criterion is designed to stabilize the system with input saturation. By matrix congruent transformation, the BMI control criterion can be changed into linear matrix inequality(LMI) criterion, then it can be easily solved by the computer. It is a one-step AW strategy that the feedback compensator and the AW compensator can be determined simultaneously. The attraction domain and its optimization are also discussed. The structure of CNNs with both constant timedelays and distribute time-delays is more general. This method is simple and systematic, allowing dealing with a large class of such systems whose excitation satisfies the Lipschitz condition. The simulation results verify the effectiveness and feasibility of the proposed method.

关 键 词：anti-windup(AW) cellular neural networks(CNNs) Lyapunov theory linear matrix inequality(LMI) attraction domain. 

分 类 号：O17[理学—数学]