Akkaya, R.Kulaksiz, A. A.Aydogdu, O.2020-03-262020-03-2620070196-8904https://dx.doi.org/10.1016/j.enconman.2006.04.022https://hdl.handle.net/20.500.12395/21326This paper presents a brushless dc motor drive for heating, ventilating and air conditioning fans, which is utilized as the load of a photovoltaic system with a maximum power point tracking (MPPT) controller. The MPPT controller is based on a genetic assisted, multi-layer perceptron neural network (GA-MLP-NN) structure and includes a DC-DC boost converter. Genetic assistance in the neural network is used to optimize the size of the hidden layer. Also, for training the network, a genetic assisted, Levenberg-Marquardt (GA-LM) algorithm is utilized. The off line GA-MLP-NN, trained by this hybrid algorithm, is utilized for online estimation of the voltage and current values in the maximum power point. A brushless dc (BLDC) motor drive system that incorporates a motor controller with proportional integral (PI) speed control loop is successfully implemented, to operate the fans. The digital signal processor (DSP) based unit provides rapid achievement of the MPPT and current control of the BLDC motor drive. The performance results of the system are given, and experimental results are presented for a laboratory prototype of 120 W. (c) 2006 Elsevier Ltd. All rights reserved.en10.1016/j.enconman.2006.04.022info:eu-repo/semantics/closedAccessphotovoltaicsMPPTDSPartificial neural networksgenetic algorithmsbrushless dc motorsArticle481210218Q1WOS:000242103800025Q1