A neural network based control strategy for flexible-joint manipulators
- 7 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1759-1764
- https://doi.org/10.1109/cdc.1989.70456
Abstract
A scheme is proposed for robust control of manipulators with flexible joints, using neural networks. A multilayer backpropagation neural network is designed and trained to compute the inverse dynamics of a flexible-joint manipulator. This network is implemented in the feedforward path. The main advantage of this scheme is that it does not require any knowledge about the system dynamics and nonlinear characteristics, and therefore it treats the manipulator as a black box. It is shown that the manipulator must be observable to ensure convergence of the neural net training procedure, and some suggestions for selecting manipulator outputs so as to make it observable are proposed. Simulation results for a single-link flexible-joint manipulator exemplify the performance of the resulting open- and closed-loop control systems.Keywords
This publication has 14 references indexed in Scilit:
- On the controllability properties of elastic robotsPublished by Springer Nature ,2005
- Learning control with neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Adaptive motion control of rigid robots: a tutorialPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Theory of the backpropagation neural networkPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1989
- On training of artificial neural networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,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
- Modeling and Control of Elastic Joint RobotsJournal of Dynamic Systems, Measurement, and Control, 1987
- A hierarchical neural-network model for control and learning of voluntary movementBiological Cybernetics, 1987
- Learning Internal Representations by Error PropagationPublished by Defense Technical Information Center (DTIC) ,1985