Constrained Point-to-Point Iterative Learning Control with Experimental Verification

Abstract

Iterative learning control is a methodology applicable to systems which perform the same operation repeatedly, where the task is the tracking of a specified reference trajectory defined over a finite time duration. Here the methodology is instead applied to the point-to-point motion control problem in which the output is only specified at a subset of time instants. The iterative learning framework is expanded to address this case, and it is shown how the extra design freedom this set-up brings allows additional input, output and state constraints to be addressed. Experimental results illustrate the practical benefits of the proposed approach, and confirm the performance and accuracy that can be achieved.

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