Constrained Point-to-Point Iterative Learning Control

Abstract

Iterative learning control is a methodology applicable to systems which repeatedly track the same reference trajectory defined over a finite time duration. Here the approach is instead applied to the point-to-point motion control problem in which the output is only specified at a subset of time instants. Iterative learning algorithms are developed to address this case, and it is shown how the extra design freedom allows input, output and state constraints to be addressed. Experimental results confirm the practicality and performance that can be achieved.

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