International Journal of Electrical and Computer Engineering (IJECE) Vol. 15, No. 5, October 2025, pp. 4355~4365 ISSN: 2088-8708, DOI: 10.11591/ijece.v15i5.pp4355-4365  4355 Journal homepage: http://ijece.iaescore.com Practical specification of the speech universe of the maximum power point tracking controller based on the asymmetrical fuzzy logic: a dynamic behavior study of the photovoltaic system Ahmed Amine Barakate, Sami Choubane, Abdelkader Hadjoudja Laboratory of Electronic Systems, Information Processing and Energetics, Ibn Tofail University, Kenitra, Morocco Article Info ABSTRACT Article history: Received Aug 7, 2024 Revised Apr 2, 2025 Accepted Jul 12, 2025 In this paper, we present a procedure for extracting data from a stand-alone photovoltaic (PV) panel to program a maximum power point tracking (MPPT) controller based on the fuzzy logic (FL) method, aiming to optimize the performance of the photovoltaic system. Photovoltaic data acquisition enables the determination of the input and output speech universe for the MPPT controller using fuzzy logic. This method adapts to nonlinear systems without requiring a complex mathematical model. Additionally, it improves the performance of the photovoltaic system in both dynamic and steady-state conditions. To further enhance the method’s efficiency, an asymmetric membership function concept is proposed based on the dynamic behavior study of the photovoltaic system. Compared to the symmetric method, the asymmetric fuzzy logic controller achieves higher maximum power output and better tracking precision. This technology is essential for maximizing photovoltaic panel efficiency, a key requirement as solar energy gains prominence as a clean and renewable energy source. Keywords: Asymmetrical fuzzy logic controller Efficiency of photovoltaic Fuzzy logic controller Maximum power point tracker Stand-alone photovoltaic system This is an open access article under the CC BY-SA license. Corresponding Author: Ahmed Amine Barakate Laboratory of Electronic Systems, Information Processing and Energetics, Ibn Tofail University Kenitra Kenitra, Morocco Email: ahmedamine.barakate1@uit.ac.ma 1. INTRODUCTION In recent years, concerns over greenhouse gas emissions and escalating fuel prices have intensified the demand for alternative energy sources. Among these, solar energy is one of the most sustainable and inexhaustible resources. However, due to the nonlinear variation of current (I) and voltage (V) characteristics of photovoltaic (PV) cells under different irradiation and temperature conditions, it is crucial to operate PV systems at specific points to extract maximum solar energy. This process, known as maximum power point tracking (MPPT), ensures efficient energy utilization. Various MPPT methods have been developed and implemented in previous studies [1]–[3], including perturbation and observation (P&O), incremental conductance, fractional open circuit voltage, fractional short circuit current, and fuzzy logic (FL) techniques. These methods offer high tracking accuracy but often face trade-offs between tracking speed and precision under varying insolation conditions. Fuzzy logic is advantageous as it does not require a precise and complicated mathematical model and can handle highly nonlinear systems. Consequently, MPPT algorithms based on FL have attracted significant research interest [4]–[7]. Recently, many MPPT techniques based on FL have been proposed in the literature. Compared to conventional algorithms, FL-based MPPT techniques demonstrate improved tracking performance, response time and power efficiency under fluctuating climatic conditions, such as