Title :
Identification and control of a robot using a neural network
Author :
Hitam, Muhammad Suzuri ; Gill, K.F.
Author_Institution :
Sch. of Ind. Technol., Univ. of Sci. of Malaysia, Penang, Malaysia
Abstract :
This paper presents a closed-loop methodology for the identification of the forward dynamics of an actual industrial robot by using a multilayer feed-forward neural network. The problems encountered when using the open loop identification procedure is highlighted and the suggestion to overcome these identified problems are then made. The indirect control scheme is employed to control the robot arm. This control scheme is based on back-error-propagation algorithm which consist of neural network identification and neural network controller. Experimental results are presented to demonstrate the capability of the neural network controller to position the robot arm
Keywords :
backpropagation; closed loop systems; feedforward neural nets; fuzzy control; fuzzy neural nets; identification; industrial manipulators; multilayer perceptrons; neurocontrollers; back-error-propagation algorithm; closed-loop methodology; feedforward neural network; forward dynamics; industrial robot; multilayer feed-forward neural network; neural network controller; neural network identification; robot arm positioning; robot control; robot identification; Automatic control; Electrical equipment industry; Feedforward neural networks; Industrial control; Multi-layer neural network; Neural networks; Open loop systems; Robot control; Robotics and automation; Service robots;
Conference_Titel :
TENCON 2000. Proceedings
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6355-8
DOI :
10.1109/TENCON.2000.888753