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.
