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Fuzzy modeling method with improved BFO and RLS


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Fuzzy modeling method with improved BFO and RLS
Li fengleiDou JinmeiLiu Fucai
Key Laboratory of Industrial Computer Control Engineering of Hebei Province,Yanshan University, Qinhuangdao 066004,China
improved bacterial foraging optimization algorithm recursive least square algorithm T-S fuzzy system global optimization
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.


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Last Update: 2014-04-30