Constrained point-to-point iterative learning control with experimental verification

Iterative learning control is a methodology applicable to systems which repeatedly track 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 conditions for convergence to zero point-to-point tracking error are derived. It is shown how the extra design freedom the point-to-point set-up brings allows additional input, output and state constraints to be simultaneously addressed, hence providing a powerful design framework of wide practical utility. Experimental results confirm the performance and accuracy that can be achieved, and the improvements gained over the standard ILC framework. (C) 2012 Elsevier Ltd. All rights reserved.