DocumentCode
3075330
Title
A neural network-based controller for a two-link robot
Author
Jamshidi, Mo ; Horne, Bill ; Vadiee, Nader
Author_Institution
Dept. of Electr. & Comput. Eng., New Mexico Univ., Albuquerque, NM, USA
fYear
1990
fDate
5-7 Dec 1990
Firstpage
3256
Abstract
A case of a multilayer perceptron (MLP) used for position control of a two-link robot is reported. Simulation results as well as the computational burden on neurocontrollers designed for robot control are presented. Such issues as the number of layers and number of nodes per layer are discussed. It is concluded that a neural network can be used to approximate a dynamical model of a robot. However, the error associated with this model is not nearly as good as that of conventional controllers, specifically a computed torque controller
Keywords
neural nets; position control; robots; torque control; dynamical model; multilayer perceptron; neural network; neurocontrollers; position control; robot; torque controller; Acceleration; Computational modeling; Computer networks; Laboratories; Manipulator dynamics; Multilayer perceptrons; Neural networks; Position control; Robot control; Torque control;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1990., Proceedings of the 29th IEEE Conference on
Conference_Location
Honolulu, HI
Type
conf
DOI
10.1109/CDC.1990.203395
Filename
203395
Link To Document