Near optimal tracking control of a class of non‐linear systems and an experimental comparison
Farshid Asadi, Ali Heydari · IET Control Theory and Applications · 2020
In this study, near optimal tracking of a class of non‐linear systems is addressed. Adaptive (approximate) dynamic programming (ADP) approach is used to calculate the optimal control in closed form. ADP has been widely used to resolve optimal regulation and tracking problems of non‐linear control systems. Despite advances in the so called supervised and unsupervised ADP techniques for optimal tracking, they have a main draw back. That is, the optimal controller needs to be recalculated for every particular reference trajectory. The main goal of this work is to address this issue for a class of non‐linear systems. Finally, this approach is applied on a Delta robot and the performance of the method is analysed experimentally.