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Proceedings Paper

Population structure of random signal-based learning for a fuzzy logic controller design
Author(s): Chang-Wook Han; Seung-Hyun Jeong; Jung-Il Park
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Paper Abstract

This paper proposes a population structure of random signal-based learning (PRSL), merged with simulated annealing (SA), to optimize the fuzzy logic controller (FLC). Random signal-based learning (RSL) exploits (local search) the search space very well, but it can not explore (global search) the search space because of its serial nature. To overcome these difficulties, PRSL, which consists of serial RSL as a population, was considered. Moreover, SA was added to RSL to help the exploration. The validity of the proposed algorithm was conformed by applying it to the optimization of a FLC for the inverted pendulum.

Paper Details

Date Published: 2 May 2006
PDF: 6 pages
Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60422D (2 May 2006); doi: 10.1117/12.664655
Show Author Affiliations
Chang-Wook Han, Yeungnam Univ. (South Korea)
Seung-Hyun Jeong, Yeungnam Univ. (South Korea)
Jung-Il Park, Yeungnam Univ. (South Korea)

Published in SPIE Proceedings Vol. 6042:
ICMIT 2005: Control Systems and Robotics
Yunlong Wei; Kil To Chong; Takayuki Takahashi; Shengping Liu; Zushu Li; Zhongwei Jiang; Jin Young Choi, Editor(s)

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