|Table of Contents|

Fuzzy modeling method with improved BFO and RLS

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2014年02期
Page:
252-258
Research Field:
Publishing date:

Info

Title:
Fuzzy modeling method with improved BFO and RLS
Author(s):
Li fengleiDou JinmeiLiu Fucai
Key Laboratory of Industrial Computer Control Engineering of Hebei Province,Yanshan University, Qinhuangdao 066004,China
Keywords:
improved bacterial foraging optimization algorithm recursive least square algorithm T-S fuzzy system global optimization
PACS:
TP13
DOI:
-
Abstract:
A hybrid learning fuzzy modeling approach based on the improved bacterial foraging optimization algorithm(IBFO)and the recursive least square(RLS)algorithm is proposed to improve the accuracy of fuzzy modeling for nonlinear system.A T-S type fuzzy system is used as the function approximator.The IBFO is used to optimize the premise parameters of the fuzzy model,and the RLS is applied to update the consequent parameters.This method realizes the global parameters optimization for fuzzy modeling.Simulation results on a nonlinear system,Box-Jenkins gas data and a pneumatic loading system show the superiority of the proposed approach in terms of approximation accuracy.

References:

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Last Update: 2014-04-30