Application of Iterative Learning Methods to Control of a LEGO Wheeled Mobile Robot

Iterative Learning Control (ILC) is a very powerful control technique that iteratively improves the transient behaviour of systems that are repetitive in nature. In this paper it is shown how ILC algorithm is designed and implemented to improve the tracking trajectory performance of mobile robot with a differential drive. Two step design procedure is proposed where a feedback controller is chosen as a classical PID controller and involves some performance specification to attenuate non-repetitive disturbances and noises. Then, as the second step, the learning filter is determined by an appropriate application of a plant inversion method. It turns out that convergence and learning performance of this ILC scheme can be obtained for a physical system and hence practical usefulness of the scheme is verified experimentally on Lego EV3-based mobile robot.