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
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;
Conference_Titel :
American Control Conference, 1999. Proceedings of the 1999
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4990-3
DOI :
10.1109/ACC.1999.786446
