Iterative Learning Control with Forgetting Factor for Linear Distributed Parameter Systems with Uncertainty

Abstract EN

Iterative learning control is an intelligent control algorithm which imitates human learning process.

Based on this concept, this paper discussed iterative learning control problem for a class parabolic linear distributed parameter systems with uncertainty coefficients.

Iterative learning control algorithm with forgetting factor is proposed and the conditions for convergence of algorithm are established.

Combining the matrix theory with the basic theory of distributed parameter systems gives rigorous convergence proof of the algorithm.

Finally, by using the forward difference scheme of partial differential equation to solve the problems, the simulation results are presented to illustrate the feasibility of the algorithm.