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
Link To Document :
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