Abstract
In this paper, an adaptive controller for robot manipulators which uses neural networks is presented. The proposed control scheme is based on PD feedback plus a feedforward compensation of full robot dynamics. The feedforward signal is obtained by summing up the weighted outputs of a set of fixed multilayer neural nets. The controller is adaptive to robot dynamics and payload uncertainties. A stability analysis which takes into account neural network learning errors is included. Simulation results showing the feasibility and performance of the approach are given. >
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