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Intelligent MPPT Control for PV Systems: A Comparative Study of Conventional and Fuzzy Logic Approaches

Intelligent MPPT Control for PV Systems: A Comparative Study of Conventional and Fuzzy Logic Approaches
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Author(s): Kiran Kumari (RNTU Bhopal, India)and Prateek Nigam (RNTU Bhopal, India)
Copyright: 2026
Pages: 24
Source title: Optimizing Automation in Engineering With Energy Systems and Communication Networks
Source Author(s)/Editor(s): Vipin Balyan (Cape Peninsula University of Technology, South Africa), Tarun Varshney (Sharda University, India), Sandeep Gupta (Graphic Era University, India)and Gunjan Gupta (Cape Peninsula University of Technology, South Africa)
DOI: 10.4018/979-8-3373-2737-2.ch006

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Abstract

This chapter presents a comparative analysis of four popular MPPT algorithms—Fuzzy Logic Control (FLC), Perturb and Observe (PNO), Incremental Conductance (INC), and Hill Climb (HC)—implemented in a MATLAB/Simulink-based PV system. The objective is to evaluate their performance under rapidly changing irradiance conditions, focusing on key metrics such as tracking speed, stability, and power extraction efficiency. Simulation results show that INC and PNO offer the most stable and efficient tracking with minimal oscillations, while FLC demonstrates superior adaptability but with slightly slower settling. The HC method exhibits slower convergence and higher ripple, making it the least effective. Overall, INC and PNO are recommended for robust MPPT control, with FLC showing potential for further development.

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