Event-triggered Control Of Several Complex Dynamic Systems

In recent years,the stability and synchronization of complex dynamic system have become one of the research focuses of scholars.It has been applied to UAV/vehicle formation control,image processing,optimization and other aspects under the condition of maintaining system dynamic behavior and achieving ideal state.However,in order to achieve system stability or synchronization,a certain amount of computation is often required,but sometimes it is limited by channel capacity and sensor efficiency.Therefore,considering the needs of practical problems and hoping to reduce the communication burden to reach the ideal state,event-triggered control strategy is introduced.Under the event-triggered control strategy,the amount of information transmission and the number of controller updates are significantly reduced,thereby reducing the communication burden.Therefore,based on the existing theories,this paper studies the event-triggered control of several kinds of complex dynamic systems.This paper focuses on the stability and synchronization of event-triggered control for several kinds of complex dynamic systems.Including the impulsive control exponential stability of linear systems based on dynamic event-triggered conditions and static event-triggered conditions、multi-delay neural network with observer based on event-triggered impulsive control and finite-time synchronization of fractional order neural networks with memristors.Through Lyapunov functional method,mathematical iteration method,mathematical inequality,Laplace transform and some matrix related knowledge,the system can be stabilized or synchronized under different controllers and event-triggered controls.The main research in this paper is as follows:The stability of a class of linear control systems under static event-triggered control,dynamic even-triggered control and impulsive control is discussed.The static event-triggered condition and the dynamic event-triggered condition are designed.By using Lyapunov functional method,the appropriate Lyapunov function is given,and the stability of the system is proved by iterative method.Finally,Zeno behavior is excludedThe synchronization and quasi-synchronization of observer based multiple neural networks with time-varying delays under event-triggered control strategy are investigated.The synchronization and quasi-synchronization of a class of state observer based multiple neural networks with time-delay and directional switching topology are studied by using impulse coupled control.An observer without time delay is designed.By constructing the corresponding augmented matrix and event-triggered impulse control scheme,synchronization and quasi-synchronization are realized.Finally Zeno is also avoided.The finite-time synchronization of fractional-order memristor neural networks under event-triggered control is studied.According to the characteristics of fractional-orde neural network,a controller for finite-time synchronization is presented.In addition,in order to reduce the amount of computation,an event-triggered control strategy is proposed.Then,finite time synchronization is obtained by fractional calculus,Lyapunov functional method and Laplace transform.Finally,avoid Zeno behavior.