An adaptive ULR fuzzy controller through reinforcement learning

Author

Tang, Zheng ; Komori, Masakazu ; Ishizuka, Okihiko ; Tanno, Koichi ; Matsumoto, Hiroki

Author_Institution

Fac. of Eng., Miyazaki Univ., Japan

Volume

3

fYear

1995

fDate

20-24 Mar 1995

Firstpage

1307

Abstract

This paper presents an adaptive fuzzy controller using unidirectional linear response (ULR) elements. The basic functions for a fuzzy controller including membership, minimum and defuzzification functions are realized by the ULR elements. Because the ULR element has a diode-like characteristics, it can be implemented by a diode-connected MOS transistor in current-mode implementations. The hardware implementation of the fuzzy controller using the ULR elements should also be very simple and straight-forward. In this paper, we also apply the ULR fuzzy controller to an inverted pendulum problem and demonstrate the effectiveness of the proposed ULR controller architecture and its learning capability through reinforcements

Keywords

adaptive control; fuzzy control; inference mechanisms; intelligent control; learning (artificial intelligence); adaptive fuzzy controller; defuzzification functions; inference system; inverted pendulum problem; membership functions; reinforcement learning; unidirectional linear response; Adaptive control; Control systems; Diodes; Fuzzy control; Fuzzy logic; Fuzzy systems; Hardware; Learning; MOSFETs; Programmable control;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1995. International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium., Proceedings of 1995 IEEE Int

Conference_Location

Yokohama

Print_ISBN

0-7803-2461-7

Type

conf

DOI

10.1109/FUZZY.1995.409851

Filename

409851