DocumentCode
2447414
Title
Optimization of a Fuzzy PI Controller using Reinforcement Learning
Author
Boubertakh, Hamid ; Glorennec, Pierre-Yves
Author_Institution
Jijel Univ.
Volume
1
fYear
0
fDate
0-0 0
Firstpage
1657
Lastpage
1662
Abstract
This paper proposes a methodology for fine tuning of the conclusion part of fuzzy proportional-integral controllers (FPIC), using both a reinforcement learning method and all the available knowledge on the process under control. Membership functions on the error domain and rule conclusions are easily defined. Therefore only the conclusion part have to be tuned
Keywords
PI control; fuzzy control; learning (artificial intelligence); fuzzy control; fuzzy proportional-integral controllers; membership functions; reinforcement learning; rule conclusions; Control systems; Fuzzy control; Fuzzy logic; Fuzzy sets; Gold; Learning; Process control; Proportional control; Three-term control; Zirconium; Fuzzy Control; Fuzzy PI Controller; Reinforcement Learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Communication Technologies, 2006. ICTTA '06. 2nd
Conference_Location
Damascus
Print_ISBN
0-7803-9521-2
Type
conf
DOI
10.1109/ICTTA.2006.1684633
Filename
1684633
Link To Document