In this paper, an intelligent control strategy for a grid connected hybrid energy generation system consisting of Photovoltaic (PV) panels, Fuel Cell (FC) stack and Battery Energy Storage System (BESS) is proposed. Firstly, the dynamic modeling of the electrical energy resources is carried out. Then, the local controllers of DC-DC power converters are designed to regulate the operating points of the energy generation units. An online-trained Elman Neural Network (ENN) based controller is developed to perform the tracking of the optimal operating point of the PV source. Moreover, a Takagi-Sugeno-Kang based fuzzy gain tuner is adopted for the adjustment of the PI parameters of the FC and BESS controllers. Besides, the Virtual Flux Oriented Control (VFOC) scheme based on neuro-fuzzy gain tuners is adopted to control the power flow between the hybrid system, the local loads and the utility grid. Furthermore, a centralized power supervisor is established to determine the levels of the power references for the local controllers according to the supply and demand conditions. The simulation results obtained in the Matlab/Simulink environment demonstrate the efficiency of the proposed control scheme. (C) 2018 Elsevier Ltd. All rights reserved.