An alternative update formula for non-linear model-based iterative learning control

Abstract

The conventional iterative learning control (ILC) algorithm for modelbased ILC of non-linear systems is presented with the use of a nonlinear inverse model as ILC compensator. The non-linear inverse model is solved with stable inversion. In addition, an alternative ILC algorithm for model-based ILC of non-linear systems is developed, also with using a non-linear inverse model as ILC compensator. Some connections between the conventional and alternative ILC algorithms and Picard, Mann and Ishikawa iterations are explored. The conventional and alternative algorithms are compared in a number of theoretical examples.