Iterative learning control

Iterative Learning Control (ILC) is a well established method used for tracking control of systems that work in a repetitive mode. Examples of systems that operate in a repetive manner include robot arm manipulators, chemical batch processes and reliability testing rigs. In each of these tasks the system is required to perform the same action over and over again with high precision.

By using information from previous repetitions, a suitable control action can found iteratively. The internal model principle yields conditions under which perfect tracking can be achieved. A typical control law is of the form:

u_p+1=u_p +K*e_p

where u_p is the input to the system during the pth repetition and e_p is the tracking error during the pth repetition.

There exists extensive literature on the theory and application of Iterative Learning Control much of which can be found via the SSILC website.