Point-to-point iterative learning control with mixed constraints

Abstract

Iterative learning control is concerned with tracking a reference trajectory defined over a finite time duration, and is applied to systems which perform this action repeatedly. In this paper iterative learning schemes are developed to address the case in which the output is only critical at certain time instants. This freedom makes it possible to incorporate both hard and soft constraints into the control scheme. Experimental results confirm practically and performance. © 2011 AACC American Automatic Control Council.