DocumentCode
1738872
Title
Indirect adaptive control of a robot using fuzzy neural network
Author
Hitam, Muhammad Suzuri ; Gill, K.F.
Author_Institution
Sch. of Ind. Technol., Univ. of Sci. of Malaysia, Penang, Malaysia
Volume
2
fYear
2000
fDate
2000
Firstpage
303
Abstract
The paper demonstrates that the fuzzy neural network can be used effectively for the control of an actual industrial robot arm. The control scheme consists of a multilayer feed-forward neural network to model the plant and a fuzzy neural network is used as a controller. The proposed design will recognise changes in process dynamic and adjust its parameters rapidly to counteract for these changes. Experimental results show that the incorporation of fuzzy logic into the network structure can provide a priori information and thereby speed up the network convergence
Keywords
adaptive control; convergence; feedforward neural nets; fuzzy control; fuzzy neural nets; industrial manipulators; multilayer perceptrons; neurocontrollers; feedforward neural network; fuzzy neural network; indirect adaptive control; industrial robot arm; multilayer feed-forward neural network; network convergence; parameter adjustment; process dynamic change recognition; robot control; Adaptive control; Feedforward neural networks; Feedforward systems; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Industrial control; Multi-layer neural network; Neural networks; Service robots;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 2000. Proceedings
Conference_Location
Kuala Lumpur
Print_ISBN
0-7803-6355-8
Type
conf
DOI
10.1109/TENCON.2000.888752
Filename
888752
Link To Document