Adaptive control of robot manipulators using fuzzy neural networks

Abstract

This paper presents an adaptive fuzzy neural controller suitable for multilink manipulators motion control. The proposed controller has the following salient features: (1) self-organizing fuzzy neural structure; (2) online learning of the robot dynamics; (3) fast convergence of tracking error; and (4) adaptive control. Computer simulation results of a two-link manipulator demonstrate that excellent tracking performance can be achieved under external disturbances.