Comparison Study of Iterative Learning Control Algorithms

来源 :The Third International Conference on Dynamics,Vibration and | 被引量 : 0次 | 上传用户:tao009
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  lterative Learning Control (ILC) is a technique of tracking control aiming at improving tracking performance for systems that work in a repetitive mode.ILC is a simple and effective control and can progressively reduce tracking errors and increase system performances from iteration to iteration.In this paper, we first classify the ILC schemes into three types: offiine learning scheme, online learning scheme, and online-offiine learning scheme.In each scheme, P-type, D-type, and PD-type learning are used to control nonlinear problems with noise and disturbance.The corresponding convergence conditions for three types of ILCs are presented.
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