  In this paper, two maximum power point tracking (MPPT) methods for Fuel Cell
(FC) systems based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and
Imperialist Competitive Algorithm trained Neural Network (ICANN) are presented.
The first operation voltage of the fuel cell corresponding to maximum power
point is determined based on the data, and then the duty cycle of a DC/DC
converter is adjusted using fuzzy logic controller to force the system that
operates in conditions which match up with its maximum power point, in order to
minimize the fuel consumption. The proposed systems and conventional fuzzy
controller system are simulated in the MATLAB environment and results show
acceptable operation under fast variation of conditions as well as normal
conditions in minimum time.
