Determining Optimal Membership Functions of a FLC-based MPPT Algorithm Using the Particle Swarm Optimization Method

被引：5

作者：

Liu, Yi-Hua ^{[1
]}

Wang, Shun-Chung ^{[2
]}

Peng, Bo-Ruei ^{[1
]}

机构：

[1] NTUST, Dept EE, Taipei, Taiwan

[2] LIIU, Dept EE, Taoyuan, Taiwan

来源：

PROCEEDINGS 2016 5TH IIAI INTERNATIONAL CONGRESS ON ADVANCED APPLIED INFORMATICS IIAI-AAI 2016 | 2016年

关键词：

fuzzy logic control; maximum power point tracking; particle swarm optimization; POWER POINT TRACKING; FUZZY-LOGIC CONTROLLER; SYSTEMS;

D O I：

10.1109/IIAI-AAI.2016.123

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Fuzzy-logic-control (FLC)-based maximum power point tracking (MPPT) algorithm can successfully deal with the transient time/tracking accuracy dilemma of the commonly utilized perturb and observe (P&O) method; however, optimal setting of the membership functions (MFs) is hard to find. In this paper, particle swarm optimization (PSO) technique is adopted to determine the optimal input MF setting values. According to the simulated and experimental results, the obtained optimal input MF values can improve the averaged MPPT tracking accuracy by 1.31 A. Moreover, the averaged fitness value can significantly be improved by 25.6 %.

引用

页码：635 / 640

页数：6

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