Title :
A neural network based feedforward adaptive controller for robots
Author :
Carelli, Ricardo ; Camacho, Eduardo F. ; Patino, Daniel
Author_Institution :
Univ. Nacional de San Juan, Argentina
fDate :
9/1/1995 12:00:00 AM
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
Keywords :
adaptive control; compensation; feedback; feedforward; manipulator dynamics; multilayer perceptrons; neurocontrollers; stability; two-term control; PD feedback; feedforward compensation; fixed multilayer neural nets; learning errors; neural network based feedforward adaptive controller; payload uncertainties; robot dynamics; robot manipulators; stability analysis; Adaptive control; Adaptive systems; Feedforward neural networks; Manipulator dynamics; Multi-layer neural network; Neural networks; Neurofeedback; Payloads; Programmable control; Robot control;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
