Discrete Iterative Learning Control With Variable Forgetting Factor for Mobile Robots

In order to improve the convergence speed of the iterative learning control method in dealing with the trajectory tracking problem of the mobile robot,this paper presents a discrete iterative learning control algorithm with variable forgetting factor.Based on the open-closed-loop iterative learning control,this algorithm adjusted the last control amount by a variable forgetting factor,and added an initial correction term with the variable forgetting factor.By adaptly choosing the initial control input in leaning rule,the initial correction term with the variable forgetting factor could avoid the amplitude swing of the iterative trajectory,thereby greatly improving the convergence speed of the iterative learning.The convergence of the algorithm was proven strictly by the norm theory,and the convergence condition in the norm form was provided.Finally,simulations verified the validity of the proposed algorithm.