Data-Driven Internal Model Controller for Mechanical Systems with Friction

摘要

In this study, we consider a data-driven controller tuning method for mechanical systems with friction. We utilize the internal model control architecture to address the undesirable effect of friction manifested as a disturbance. We then apply virtual reference feedback tuning (VRFT), which enables us to obtain an optimal controller for the desired tracking property by using only one-shot experimental data. We also demonstrate that it is possible to obtain both the desired controller and a suitable mathematical model of the plant by applying the internal model controller with a friction compensator. Furthermore, we present experimental results to validate the proposed method.