Maximum Power Point Tracking control of PV system for DC motors drive with Neural Network

This paper presents an application of a Neural Network(NN) for Maximum Power Point Tracking (NTPT) of PV supplied DC motor. A variation of solar irradiation is most important factor in the NTPT of PV system. That is nonlinear, aperiodic and complicated. NN was widely used due to easily solving a complex math problem. The paper consists of solar radiation source, DC-DC converter, DC motor and load(cf, pump). NN algorithm apply to DC-DC converter through an Adaptive control of Neural Network, calculates Converter-Chopping ratio using an Adaptive control of NN. The results of an Adaptive control of NN compared with the results of Converter-Chopping ratio which are calculated mathematical modeling and evaluate the proposed algorithm. The experimental data show that an adequacy of the algorithm was established through the compared data.