In the last two decades, the maximum power point tracking (MPPT) methods for PV system is becoming very interesting subject. Among these methods there is Fuzzy-MPPT, which is mainly based on two inputs and at least 25 rules. This structure need more calculation time and not easy to be implemented in hardware. For these reasons and in order to facilitate the MPPT synthesis, this paper proposes an intelligent MPPT controller based on a single-input Takagi-Sugeno fuzzy logic controller (SI-TS-FLC) with three linguistic variables and three rules. The proposed controller is simulated using MATLAB-SIMULINK for a PV system, which consists of a PV generator, DC-DC converter, and resistive load under varied temperature and irradiance levels. An experimental study is conducted using DSPACE 1104 card real-time board under partial shading condition. Simulation and experimental results show that the proposed controller exhibits less settling time and lower overshoot than the commonly used perturb and observe (P&O) algorithm in the transient state and minimum oscillation around the optimal operating point. Index Terms-Fuzzy control; Maximum power point trackers; Photovoltaic systems; Takagi-Sugeno model. I. INTRODUCTION Currently, environment pollution issues, particularly climate change, cannot be neglected. According to many scientists, climate change is mainly due to the disastrous effects of emissions of greenhouse gases, particularly CO2, which are responsible for global warming and increase in the earth's temperature. Global warming causes several natural cataclysms, such as floods, cyclones, soil erosion, and losses in genetic diversity, in several locations worldwide. These natural disasters present an unprecedented ecological threat