DocumentCode
343298
Title
Reinforcement tuning of type II fuzzy systems
Author
Davis, Cleon ; Peng, Pei-Yuan
Author_Institution
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume
4
fYear
1999
fDate
1999
Firstpage
2315
Abstract
A type II fuzzy system is refined by a reinforcement learning scheme in the paper. By tuning the parameters of the type II fuzzy controller, we demonstrate that reinforcement learning can help to achieve good performance. Results from the pole-balancing problem are given with comparisons of different fuzzy control schemes. It is shown that the learned type II fuzzy controller can achieve goals as well as others
Keywords
fuzzy control; fuzzy logic; fuzzy systems; learning (artificial intelligence); nonlinear control systems; position control; tuning; pole-balancing problem; reinforcement learning scheme; reinforcement tuning; type II fuzzy controller; type II fuzzy systems; Control systems; Decision making; Equations; Fuzzy control; Fuzzy systems; Optimal control; State-space methods; System performance; Training data; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 1999. Proceedings of the 1999
Conference_Location
San Diego, CA
ISSN
0743-1619
Print_ISBN
0-7803-4990-3
Type
conf
DOI
10.1109/ACC.1999.786446
Filename
786446
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