This paper presents a novel learning feed-forward controller design approach for accurate robotics trajectory tracking. Based on the joint nonlinear dynamics characteristics, a model-free learning algorithm based on Support Vector Machine (SVM) is implemented for friction model identification. The experimental results verified that SVM based learning feed-forward controller is a good approach for high performance industrial robot trajectory tracking. It can achieve low tracking error comparing with traditional trajectory tracking control method.
D. Bi, G. L. Wang, Jun Zhang, Q. Xue