Guaranteed cost iterative learning control — An application to control of Permanent Magnet Synchronous Motors

Abstract

This paper addresses the design of iterative learning control laws (ILC) for both trial-to-trial error convergence and along-the-trial performance. It is shown how these control laws can be designed using the theory of discrete linear repetitive processes in combination with a guaranteed cost control approach. The parameterization of the controllers is performed by the solution of linear matrix inequalities (LMIs). The paper is concluded with experimental results for the position control of a Permanent Magnet Synchronous Motor (PMSM).