DocumentCode :
3584822
Title :
Combined approach between FLC and PSO to find the best MFs to improve the performance of PV system
Author :
Rahma, Ayat ; Khemliche, Mabrouk
Author_Institution :
Electr. Eng., Dept., Univ. of Setif 1, Setif, Algeria
fYear :
2014
Firstpage :
1
Lastpage :
8
Abstract :
During designing of fuzzy logic controller (FLC), an expert knowledge of the process to be controlled can be used to determine the membership functions (MFs) and the rules. However there is no general procedure for designing a FLc seen that many of errors may be encountered in its implementation, and these FLC can not be adapted to other applications. The difficulties encountered in the design of CLF have guided researchers to move towards the optimization of these controllers. The present paper proposes an approach combined from FLC and particle swarm optimization algorithm (PSO) used to finding the optimum membership functions (MFs) of a fuzzy system with the aim of achieving the accurate and acceptable desired results. For improving and optimizing the performance of a photovoltaic system to deliver the maximum power available. It is clearly proved that the optimized MFs provided better performance than a fuzzy model for the same system, when the MFs were heuristically defined.
Keywords :
fuzzy control; maximum power point trackers; particle swarm optimisation; photovoltaic power systems; FLC; MF; MPPT; PSO; PV system; fuzzy logic controller; fuzzy system; maximum power point trackers; membership functions; particle swarm optimization algorithm; photovoltaic system; Electrical engineering; Fuzzy logic; Gold; Laboratories; Maximum power point trackers; Sociology; Statistics; Fuzzy logic control (FLC); MPPT; Membership functions (MFs); Particle swarm optimization (PSO); Photovoltaic system (PV);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Sciences and Technologies in Maghreb (CISTEM), 2014 International Conference on
Type :
conf
DOI :
10.1109/CISTEM.2014.7077038
Filename :
7077038
Link To Document :
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