Iterative learning algorithm research with forgetting factor for systems with control delay
控制时滞系统的遗忘因子迭代学习算法研究

In this paper, the thought that the forgetting factor is a function of the number of iterations is proposed, which has simplified the convergence conditions of the traditional iterative learning control algorithm with forgetting factor and its convergence analysis is given. Then, the iterative learning control algorithm with forgetting factor whose convergence conditions are improved is applied to a class of linear systems with control delay, and simulation examples are given. Simulation results show that, under the improvements of the convergence conditions and the reasonable choice of forgetting factor function, the PD-type iterative learning control algorithm with forgetting factor applied to the linear systems with control delay in this paper has effectiveness and superiority.