In this paper, a maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems is achieved based on fuzzy logic controller (FLC) and compared with an anfis (neuro-fuzzy) based mppt controller, this method allies the abilities of artificial neural networks in learning and the power of fuzzy logic to handle imprecise data. Both methods are simulated using matlab/ simulink. The choise of power variation and the current variation as inputs of the proposed controllersreducesthe calculation. Both FLC and ANFIS based MPPTare tested in terms of steady state performance and the pv system dynamic.

<p><span lang="EN-US">This paper presents a fuzzy logic controller for maximum power point tracking (MPPT) in photovoltaic system with reduced number of rules instead of conventional 25 rules to make the system lighter which will improve the tracking speed and reduce the static error, engendering a global performance improvements. in this work the proposed system use the power variation and current variation as inputs to simplify the calculation, the introduced controller is connected to a conventional grid and simulated with MATLAB/SIMULINK. The simulation results shows a promising indication to adopt the introduced controller as an a good alternative  to traditional MPPT system for further practical applications</span></p>