Learning Control Of Nonlinear Parametric System Based On Unknown Control Direction

In the field of intelligent control,learning control is an important part,among which iterative learning control and repetitive learning control are the most representative.Repetitive learning control and iterative learning control are two and common methods and means that can effectively deal with the repeatability and periodicity of the control system.The control target can make the controlled system track the known target track completely in a limited(or infinite)time interval.The basic idea is to improve the current iteration by the information obtained from the last iteration(or period)of the controlled system Control input of generation(or period).The adaptive control method can effectively deal with the tracking control problem of nonlinear dynamical systems with time invariant parameters.The recently developed adaptive iterative learning control combines adaptive control with iterative learning control,which can effectively deal with the tracking control of nonlinear systems.In this paper,adaptive iterative learning control method is used to study some nonlinear systems with unknown control direction.The main work of this paper is as follows:Firstly,An adaptive iterative learning control method is proposed for a class of first-order hybrid linear and nonlinear parametric nonlinear systems with unknown control direction.Under the condition of alignment,the tracking error of the system tends to zero.In the design of controller,Nussbaum gain technology and method are used to solve the problem of unknown control direction.Difference is introduced The Lyapunov compound energy function theory is used to solve the stability of the system.Secondly,On the basis of the above,it is further extended to solve the adaptive learning control problem of a class of high-order mixed linear and nonlinear parametric nonlinear systems with unknown control direction.Nussbaum method is used to solve the problem of unknown control direction in the system.Then,Lyapunov composite energy function is used to prove the stability and error convergence of the controlled system.Thirdly,On the basis of the above,the adaptive learning control of a class of first-order hybrid bilinear and nonlinear parametric nonlinear systems with unknown control direction is studied.With the help of Nussbaum function design method,the corresponding adaptive iterative learning control is proposed to deal with the problem of unknown control direction in the system.With inequality technique,the parameter adaptive law is designed to effectively solve the problem The disturbance of time-varying parameter uncertainty is included in the system,and the stability of the closed-loop system is proved by Lyapunov compound energy function theory.Fourthly,On the basis of the above,it is further extended to solve the adaptive learning control problem of a class of high-order hybrid bilinear and nonlinear parametric nonlinear systems with unknown control direction.Using Nussbaum function method and properties,an adaptive iterative learning control algorithm is designed.Based on the construction of Lyapunov composite energy function,the stability and Boundedness of the closed-loop system are proved.Finally,the feasibility and effectiveness of each algorithm are verified by simulation.