Artificial Neural Networks for Iterative Learning Control

As we have noted, the real usefulness of iterative learning control is for problems in which we wish to control the transient response behavior of nonlinear or time-varying systems. In this case it makes sense to consider learning controllers that also have a nonlinear or time-varying structure, such as the learning control scheme demonstrated in the previous chapter. A non-trivial question, however, is what type of nonlinear system should be considered. The class of all nonlinear systems is very large and it is not clear what structure would work best for learning control applications. One answer to this question is to consider the class of nonlinear systems called artificial neural networks. Artificial neural networks, with their nonlinear structure and their ability to learn internal representations and recall associations, are good candidates for nonlinear learning control.