The Strategy Research Of Iterative Learning Control For Robot

Iterative learning control, as a branch of the intelligent control, is a technique for improving the transient response performance of system or processes that operate repetitively over a fixed time interval. Iterative learning control it refines the next control input using the information such as current control input and error signals after each trial until the specified desired trajectory is followed to a high precision. Many researchers have paid their attentions to it because of the simplicity and effectiveness. In recent years, it has developed quickly and been used widely. The most leading application of iterative learning control is in the robot.Tracking control is a very important working model for the robot repeating working. To deal with the tracking control of robot which executes the repeating work, the paper is proposed the iterative learning control strategy. So we can get the high performance and more quick convergence.This paper is to find an effective analytical method, solving the kinematics and inverse kinematics of 3-link robot. And we also establish precise dynamic model.Especially, we present the PID-Type iterative learning control scheme and the proof of its convergence in order to introduce the basic principle of iterative learning control. Based the basic D -type ILC, an effective improved Iterative Learning Control rule is propose. A convergence gene has been added into the D -type ILC for getting high convergence rate. The simulation of robot show that the proposed Iterative Learning Control rule is applied to the tracking control of the 2-link model of robot manipulator and good tracking performance is obtained .Last, the work of this paper is to research an open-closed loop PD-type and D-type iterative learning control algorithm for a class of non-linear time-varying system and its application for robot. And the simulation for a robot system shows the feasibility and effectiveness...