A Predictive control based on Neural Network for Proton Exchange Membrane Fuel Control

Non-polluting energy generation and other environmental consequences have been driving an increasing demand for new energy conversion technologies during the last few years .Within such perspective fuel cells (FC) have been appeared as an ideal alternative because of their high generation efficiency , high generation power density , no-noise ,zero pollution , module type structure and high reliability and durability. Proton Exchange Membrane Fuel cell (PEMFC) is a kind of fuel cells that directly transforms chemical energy of hydrogen and oxygen into electrical energy through electrochemical reactions without burning and has some other special advantageous made it a great alternative for automotive and movable applications. Because of amending of PEMFCs performance and increasing safety and reliability a satisfying control on PEMFC must be done. Traditional controllers couldnt lead to acceptable responses because of timechange, long- hysteresis, uncertainty, strong- coupling and nonlinear characteristics of PEMFCs. So an intelligent or adaptive controller is needed. In this paper a neural network predictive controller have been designed to control the voltage of fuel with varying load and at the presence of fluctuations.