Stability Analysis And Control Design For Several Kinds Of Uncertain Neutral Neural Networks With Time-varying Delays

Time delay is widespread in nature.It is an inevitable phenomenon.The study on time delay system has important theoretical significance and application value,especially the system with time-varying delay.This paper aims to study the stability and control design for an uncertain neutral neural network with time-varying delay.The main conterts and research results are as follows:Firstly,the problem of exponential stability and stabilization for switched neutral neural network system with time-varying delay and norm bounded uncertainties is studies in this paper.Based on linear matrix inequality technique,Newton Leibniz formula,free weighing matrix method and the average dwell time approach,new criteria are established to guarantee the global exponential stability for a class of switched neutral neural network by constructing a novel Lyapunov-Krasovskii functional.In addition,based on state feedback control,new sufficient condition is derived,which guarantee the uncertain switched neutral neural network system with time-varying delay is exponential stabilizable.The condition ensures the corresponding closed-loop system is exponential stable.Furthermore,by using some matrix transformation method,a design method of control feedback gain matrix is presented in this paper.Finally,numerical example is given to demonstrate the effectiveness of the results.Secondly,the exponential stabilization for a class of uncertain neutral neural network with mixed interval time-varying delays is investigated by periodically intermittent control in this paper.By constructing an appropriate Lyapunov-Krasovskii functional,using Jensen inequality and some useful lemmas,the exponential stabilization problem for a class of neutral neural networks with uncertainty is studied and new delay-dependent criteria is derived to ensure the exponential stability of corresponding closed-loop system.In addition,based on the proposed criteria,an intermittent state feedback controller design approach is also presented in terms of linear matrix inequalities technique.Finally,two numerical examples are solved by MATLAB software and the simulation results are given.Finally,the problem of finite-time stability and stabilization is investigated for a class of neutral neural network with time-varying delay and parameter uncertainties in this paper.First of all,by establishing a novel Lyapunov-Krasovskii functional,using linear matrix inequality technique and some useful lemmas,the sufficient condition for the finite-time stability of a class of neutral neural network is presented.Then,based on state feedback control,new criteria are established which guarantee the uncertain neutral neural network with time-varying delay is finite-time stable by employing the method of matrix transformation.Furthermore,the design method of the control gain matrix is given to ensure the finite-time stability of the corresponding closed loop system.Finally,the numerical simulation examples are given to show the effectiveness of the theoretical results.