Research On Event-triggered Impulsive Control And Finite-time Control Of Complex Systems

Complex systems can easily be found everywhere in engineering applications,for example,general nonlinear systems,neural network systems,multi-agent sys-tems and so on.At present,with the rapid development of complex systems and its applications in many fields and disciplines,the research contents and research methods of complex systems are being continually updated,where event-triggered control and finite-time control are both effective control methods in modern control theory.This paper mainly considers event-triggered impulsive control and finite-time control of complex systems.The outline of the rest of this paper is as followsIn Chapter 1,we mainly introduce the background and significance of our research topic,the main research content of this paper,and some important def-initions and lemmas are needed to be used.In Chapter 2.firstly,we establish the basic theory of event-triggered impulsive control strategy based on Lyapunov stability.With the theory of impulsive control and Lyapunov method,some suf-ficient conditions are given to guarantee the uniform stability(US)and globally asymptotical stability(GAS)of systems,respectively,where a class of forced im-pulse sequence is involved in the design of event-triggering mechanism(ETM)to ensure the asymptotic behaviour.Moreover,Zeno behaviour can be excluded in those results.Secondly,as for applications,we apply the theoretical results to the consensus problem of multi-agent systems and stability analysis of nonlinear im-pulsive control systems.Finally,several numerical examples and theirs simulations are provided to demonstrate the effectiveness of our proposed results.In Chapter 3,the problem on finite-time synchronization of Cohen-Grossberg neural networks(CGNNs)with mixed time delays is studied.First,we consider a single CGNN.By constructing a suitable Lyapunov-krasovskii functional candidates and using some mathematical inequalities,a discontinuous state feedback controller is designed for the response system to ensure finite-time synchronization with the drive system of CGNNs.Secondly,inspired by the above results,we consider the coupling CGNNs.In the model of neural networks with state coupling,a discontinuous controller is designed to synchronize the response system and the drive system in finite time.Finally,examples with numerical simulation are given to illustrate the validity of our research results.