Fast Algorithm of Open-Closed Loop PD-type Iterative Learning Control for DC motor

摘要

A fast algorithm of open-closed loop PD-type iterative learning control (ILC) for a class of nonlinear system is proposed in the paper. In the algorithm, the system's current tracking error and previous tracking error and their differential signals are all used to update the control law meanwhile. At the same time, the control law applies varying proportion parameters, which can be adjusted according to the system's errors. Therefore, the capability of the target tracking is greatly improved. Then the sufficient condition for the convergence of the proposed fast iterative learning algorithms is given. Finally simulation results for DC motor show the validity and feasibility of the proposed algorithm.