Robust control of high gain DC-DC converter using Type-2 fuzzy neural network controller for MPPT

Article type: Research Article

Authors: Kececioglu, O. Fatih^{; *}

Affiliations: Department of Electrical and Electronics Engineering, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey

Correspondence: [*] Corresponding author. O. Fatih Kececioglu, Department of Electrical and Electronics Engineering, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey. E-mail: [email protected].

Abstract: Maximum Power Point Tracking (MPPT) is one of the major functions of PV system because of the performance of PV system directly affected by atmospheric conditions. This paper first presents a novel configuration for MPPT of PV system. This configuration is combined with modified positive luo converter that is high gain dc-dc converter and Type-2 fuzzy neural network controller (T2FNNC). Modified positive luo converter that has high voltage gain and conversion efficiency is suitable for the two-stage grid integrated solar photovoltaic system. The main advantage of proposed configuration is high performance and stability against to disturbance inputs such as solar radiation and panel temperature variations. To validate the performance of this configuration, a simulation model is built by using Matlab/Simulink. The simulation results show that proposed configuration based on modified positive output luo converter with T2FNN has a superior performance than conventional PI controllers in terms of MPP tracking efficiency under changing atmospheric conditions.

Keywords: Robust control, Type-2 FNN, MPPT, modified positive output Luo converter

DOI: 10.3233/JIFS-181770

Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 941-951, 2019