Nonlinear systems design by a novel fuzzy neural system via hybridization of em and PSO algorithms

Ching Hung Lee*, Jun Hao Liang, Yu Chia Lee

*此作品的通信作者

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

In this paper, we propose a hybridization of electromagnetism-like mechanism (EM) and particle swarm optimization algorithm (PSO) algorithms to design the proposed functional-link based Petri recurrent fuzzy neural system (FLPRFNS) for application of nonlinear system control. The FLPRFNS has a TSK-type fuzzy consequent part which uses functional-link based orthogonal basis functions and a Petri layer is added to eliminate the redundant fuzzy rule for each input. In addition, the FLPRFNS is trained by a hybrid algorithm-modified EMPSO. The main modification is that the randomly neghiborhoodly local search is replaced by particle swarm optimization algorithm with an instant update particles velocity strategy. Each particle updates its velocity instantaneously one by one and every particle can get best information from system. The modified EMPSO combines the advantages of multipoint search, global optimization, and faster convergence. Simulation results show that the modified EMPSO has the ability of golbal optimization, advantages of faster convergence and FLPRFNS has effect of higher accuracy.

原文English
主出版物標題Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010
頁面19-24
頁數6
出版狀態Published - 2010
事件International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010 - Kowloon, Hong Kong
持續時間: 17 三月 201019 三月 2010

出版系列

名字Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010

Conference

ConferenceInternational MultiConference of Engineers and Computer Scientists 2010, IMECS 2010
國家/地區Hong Kong
城市Kowloon
期間17/03/1019/03/10

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