DocumentCode
304100
Title
A predictive fuzzy relational controller
Author
Bourke, Mary M. ; Fisher, D.G.
Author_Institution
Dept. of Chem. Eng., Alberta Univ., Edmonton, Alta., Canada
Volume
2
fYear
1996
fDate
8-11 Sep 1996
Firstpage
1464
Abstract
The fuzzy controller proposed in this paper has the same structure as a conventional model-based predictive controller but uses a relational-based model which is superior to rule-based models in that it: permits numerical and analytical analysis; employs the max-product compositional operator which gives better results, using a minimum distance criterion than the traditional max-min compositional operator; and includes self learning (fuzzy identification) capabilities. Simulation results show that this fuzzy controller gives better performance than a gain-scheduled PI (proportional plus integral) controller when applied over the full operating range of a continuous nonlinear process
Keywords
fuzzy control; continuous nonlinear process; fuzzy identification; max-product; minimum distance criterion; predictive fuzzy relational controller; relational-based model; self learning; Adaptive control; Feedback; Filters; Fuzzy control; Optimal control; PD control; Pi control; Predictive control; Predictive models; Proportional control;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location
New Orleans, LA
Print_ISBN
0-7803-3645-3
Type
conf
DOI
10.1109/FUZZY.1996.552391
Filename
552391
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