Adaptive Inverse Control of Proton Exchange Membrane Fuel Cell Using RBF Neural Network

摘要

Proton exchange membrane fuel cells (PEMFCs) present remarkable control demands, due to theinherent nonlinear characteristics and time-varying parameters. This paper deals with the application ofadaptive inverse control using radial basis function neural network (RBFNN) to PEMFC system. Thiscontrol scheme has the advantage of not needing to identify the dynamical parameters of the systemfor design and scheduling of the controller parameters. In order to improve the control aim and toguarantee the closed loop stability as well as system robustness a feedback PD controller is combinedwith the RBF-based adaptive inverse control. Results from the simulation manifest that the inversecontrol scheme is promising technique and can ensure the satisfactory performance.