Training Neuro-Fuzzy by Using Meta-Heuristic Algorithms for MPPT

作     者：Ceren Baştemur Kaya Ebubekir Kaya Göksel Gökkuş 

作者机构：Department of Computer TechnologiesNevsehir Vocational CollegeNevsehir Haci Bektas Veli UniversityNevşehir50300Turkey Department of Computer EngineeringFaculty of Engineering and ArchitectureNevsehir Haci Bektas Veli UniversityNevşehir50300Turkey Department of Electrical and Electronics EngineeringFaculty of Engineering and ArchitectureNevsehir Haci Bektas Veli UniversityNevşehir50300Turkey 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2023年第45卷第4期

页      面：69-84页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

主　　题：Optimization meta-heuristic algorithm neuro-fuzzy MPPT photovoltaic system 

摘      要：It is one of the topics that have been studied extensively on maximum power point tracking(MPPT)*** or soft computing methods are used for *** soft computing approaches are more effective than traditional approaches,studies on MPPT have shifted in this *** study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for *** meta-heuristic training algorithms used are particle swarm optimization(PSO),harmony search(HS),cuckoo search(CS),artificial bee colony(ABC)algorithm,bee algorithm(BA),differential evolution(DE)and flower pollination algorithm(FPA).The antecedent and conclusion parameters of neuro-fuzzy are determined by these *** data of a 250 W photovoltaic(PV)is used in the *** effective MPPT,different neuro-fuzzy structures,different membership functions and different control parameter values are evaluated in *** training algorithms are compared in terms of solution quality and convergence *** strengths and weaknesses of these algorithms are *** is seen that the type and number of membership function,colony size,number of generations affect the solution quality and convergence speed of the training *** a result,it has been observed that CS and ABC algorithm are more effective than other algorithms in terms of solution quality and convergence in solving the related problem.