Adaptive Asymptotic Tracking Control For Periodic Time-varying Disturbance Systems With Input Delay

In the actual control system,such as power system,communication system,network transmission system,mechanical control system and industrial system,there are widely nonlinear uncertainty and delay problems,these two kinds of problems will affect the performance and stability of the system.For nonlinear control systems with time delay,this research has certain significance.In addition,for uncertain nonlinear systems,the study of periodic time-varying perturbations remains an extremely challenging problem,and the research results in this field are very limited.In view of this,this dissertation investigates the adaptive asymptotic tracking control problem for two types of uncertain input time-delay systems with periodic time-varying perturbations.The main research and novelty points of this paper include:(1)The adaptive asymptotic tracking control problem is considered for a type of uncertain input time-delay systems with periodic time-varying disturbances.By combining Fourier series expansion(FSE)with radial basis function neural network(RBFNN),a mixed function approximator(FSE-RBFNN)is constructed to approximate the function with periodic time-varying disturbances.At the same time,the dynamic surface control technique with nonlinear filter is deployed to eliminate the “complexity explosion” problem.Under the action of the designed control strategy,all signals in the system are semi-globally uniformly bounded,and the actual output signals of the system can be asymptotically tracked to the pre-given system reference signal.Finally,the practicality of the above design strategy is certified by matlab simulation example.(2)For a class of periodic disturbance switched systems with sensor faults,the eventtriggered control problem of the system is studied.The Pade approximation technique is used to solve the input time delay problem,and a hybrid function approximator(FSE-RBFNN)is constructed to approximate the function with periodic disturbance online.At the same time,the DSC technique with nonlinear filter is proposed to eliminate the “complexity explosion”problem.The event-triggered mechanism is introduced to reduce the data transmission and communication without affecting the system performance.Under the application of the designed control strategy,the tracking error is reduced to a predetermined tracking precision,and all signals in the system are semi-globally uniformly bounded.Finally,the practicality of the above design strategy is certified by matlab simulation example.