Puren R. Ouyang
Iterative learning control, PD feedback control, trajectory tracking, convergence, nonlinear system
In this paper, a new iterative learning control, called PD-PD type iterative learning control, is proposed for trajectory tracking of time-varying nonlinear systems with no-repetitive uncertainty and disturbance. In the developed control scheme, a PD feedback controller using current tracking errors and a PD-type iterative learning controller based on previous tracking errors are combined in the proposed updating law. Explicit expressions have been developed for choosing the feedback control gains and the learning control gains. It is proven that the final tracking error is guaranteed and the tracking trajectory converges towards the desired one in the presence of uncertainty and disturbance. In addition, an initial updating scheme is adopted to reduce and eliminate initial errors from iteration to iteration. The proposed PD-PD type learning control has potential benefits for real applications, which include faster convergence rate, more flexible choices of the learning gains and monotonic convergence of tracking errors. The effectiveness of the proposed control law is demonstrated by simulation experiments.
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