DocumentCode
296060
Title
Elastic fuzzy logic for self-learning control systems
Author
Beigy, Hamid ; Eydgahi, Ali M. ; Katebi, S.D.
Author_Institution
Comput. Eng. Dept., Shiraz Univ., Iran
Volume
1
fYear
1995
fDate
Nov/Dec 1995
Firstpage
622
Abstract
In this paper, an adaptive network based on elastic fuzzy logic for control systems has been proposed. An expert initializes the network and then network´s weights are obtained by using neural network methods. An example of truck backer is given to illustrate the proposed method. In this example, we used the widrow´s method for calculating the controller output error
Keywords
fuzzy control; fuzzy neural nets; neurocontrollers; self-adjusting systems; unsupervised learning; adaptive network; elastic fuzzy logic; self-learning control systems; widrow´s method; Adaptive control; Adaptive systems; Control systems; Elasticity; Error correction; Fuzzy logic; Humans; Input variables; Multi-layer neural network; Neural networks; Nonlinear dynamical systems; Programmable control;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488251
Filename
488251
Link To Document