Modified optimal control with a backpropagation network for robotic arms

Abstract

In this study, the trajectory tracking problem of robotic arms is considered. To solve this problem, two novel modified optimal controllers based on neural networks are proposed. The uniform stability of both the tracking error and approximation error for the aforementioned controllers is guaranteed by means of a Lyapunov-like analysis. The effectiveness of the proposed controllers is verified by simulations.