Abstract
This paper presents a new control scheme utilizing fuzzy neural networks for trajectory control of robot manipulators. The adaptive capability of the fuzzy neural controller ensures that high performance can be achieved and maintained under time-varying conditions. This intelligent control scheme consists of two portions. In the first portion, the fuzzy neural networks with dynamic structure, in short DFNNs, are constructed to estimate dynamics of the robot model. The second portion is the fuzzy neural controller, which is built based on model learning and on-line weight adjustment. Computer simulations of a two-link robot manipulator demonstrate the effectiveness and efficiency of the proposed scheme.