Experimental neural decomposed dynamic adaptive control of robot manipulator
Authors:
- B. BouzouiaBBB. Bouzouia
- M. KadriMKM. Kadri
- N. LouamNLN. Louam
- 20 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, 488-493
Abstract
We investigate a new neural network decomposed dynamic adaptive controller for the robot manipulator. The robot controller is divided into two components. The dynamic action is based on the decomposition of dynamical model into fixed and variable torque. The fixed torque represents the nominal torque and the variable torque, based on the parameter estimation obtained with an ANN, tracks the change in the dynamical system. To estimate the variable parameters we used an ANN parameter estimator. Two schemes were derived from this approach and applied successfully to a SCARA robotKeywords
This publication has 13 references indexed in Scilit:
- Experimental implementation of neural network controller for robot undergoing large payload changes2002
- Adaptive versus neural adaptive control: Application to roboticsInternational Journal of Adaptive Control and Signal Processing, 1994
- Trajectory control of robotic manipulators using neural networksIEEE Transactions on Industrial Electronics, 1991
- Neural network payload estimation for adaptive robot controlIEEE Transactions on Neural Networks, 1991
- Identification and control of dynamical systems using neural networksIEEE Transactions on Neural Networks, 1990
- 30 years of adaptive neural networks: perceptron, Madaline, and backpropagationProceedings of the IEEE, 1990
- Decentralized adaptive control of manipulators: theory, simulation, and experimentationIEEE Transactions on Robotics and Automation, 1989
- Hierarchical neural network model for voluntary movement with application to roboticsIEEE Control Systems Magazine, 1988
- A multilayered neural network controllerIEEE Control Systems Magazine, 1988
- An introduction to computing with neural netsIEEE ASSP Magazine, 1987