Adaptive Iterative Learning Fault-tolerant Control For A Class Of Nonlinear Systems

As an intelligent control method,Iterative Learning Control has become one of the hot issues in the field of nonlinear control due to its remarkable advantages and good control performance.It has been paid more and more attention by many researchers and has been widely used.Based on iterative learning control method as the main means to study a class of nonlinear parametric system adaptive iterative learning fault-tolerant control problems,on that basis,the proposed controller design method is extended to the multi-agent system,and the consistency problem of a class of multi-agent system is studied.The main work of this paper includes:(1)The adaptive iterative learning fault-tolerant control problem is studied for a class of nonlinear parameterized systems with time delay and actuator faults.Firstly,for SISO system,the nonlinear items such as time-varying delay,nonlinear parameters and actuator failure are considered,using parameter separation technology,these nonlinear terms are separated and transformed,on this basis,an adaptive iterative learning fault-tolerant controller and a new parameter updating law on the iterative domain are constructed;Second,the design idea of iterative learning controller of SISO system is extended to multi-input multi-output(MIMO)system,a reliable adaptive iterative learning control strategy is designed to deal with nonlinear disturbances caused by time delay and actuator fault and the coupling effect between the output information of the system is dealt with by using the relative knowledge of the matrix;Then,the asymptotic convergence of the state tracking error along the iterative axis and the closed-loop signal bounded property of the SISO and MIMO systems are proved by using the compound energy function(CEF).Finally,the correctness and effectiveness of the proposed control strategy are verified by numerical simulation.(2)For a class of multi-agent systems with time delay,input saturation and actuator fault,which the consistency problem is studied under the background of repeated operation of the system.Firstly,by defining the extended tracking error of multi-agent,and aiming at the uncertainty problems caused by various constraints in multi-agent system,a distributed adaptive iterative learning fault-tolerant controller with fully saturated parameter updating law was constructed.Then,by constructing a new compound energy function to prove the convergence of tracking error of multi-agent system.Finally,the effectiveness and correctness of the proposed control scheme are verified by comparing the typical iterative learning controller with the controller designed in this paper.The results show that the adaptive iterative learning fault-tolerant controller proposed in this paper can effectively reduce the number of iterations and tracking errors.