Event-triggered Adaptive Control For Uncertain Nonlinear Systems

In complex control systems,network congestion,transmission delay and other problems usually occur when the amount of information is large and the network bandwidth is limited,which leads to the degradation of system performance.In the main strategies for this problem,the event-triggered control strategy focuses on the current operating state of the system,and only when the triggerring condition is met can signals are transmitted and updated.Thus,the event-triggered control strategy is more effective in saving resources(such as system resources,network resources,etc.).At present,event-triggered control strategy has achieved good results in linear systems.However,there are still some problems to be solved in the event-triggered control for nonlinear systems,e.g.,although uncertain factors such as unknown parameters,stochastic noise and so on generally exist in the actual system,the results of event-triggered control for the uncertain nonlinear system are still insufficient.Therefore,this paper mainly focuses on the above problems,considering the problem of event-triggered adaptive control for nonlinear uncertain system with unknown parameters and random disturbances to ensure the performance of the system while reducing the update frequency of the control signal and avoiding the Zeno phenomenon.Firstly,the problem of event-triggered adaptive control for uncertain nonlinear systems is studyed,when there are unknown parameters in the system.Then using the Backstepping algorithm to recursively design adaptive laws to estimate unknown parameters.At the same time,based on the control input signal error,the fixed threshold strategy and the relative threshold strategy that the triggering threshold follows the linear change of the control input signal amplitude are designed.In order to address the problem that the switching of the relative threshold strategy may produce large step signal,the adaptive threshold strategy that can adjust the threshold automatically is proposed,which ensures that the closed-loop signal is globally bounded,the tracking error converges to an adjustable compact set arround the origin,the update frequency of the control signal is reduced and the Zeno phenomenon can be avoid.Secondly,the event triggered adaptive control algorithm is established based on the system state error for a class of nonlinear system with random disturbance,to realize that the system perforcemance is guaranteed,and network load can be reduced,the Zeno phenomenon can be avoided simultaneously.Finally,the event-triggered adaptive control for nonlinear systems under complex uncertainties is further studied,when the system has both unknown parameters and random disturbances with unknown covariance.The effectiveness of the established event-triggered adaptive control algorithm was verified by MATLAB simulation.Since most practical systems are nonlinear,and there are inevitably uncertain factors such as unknown system parameters and random disturbances,the research on the event triggered adaptive control of uncertain nonlinear system in this paper is theoretical and more practical in physics.