Abstract
In this part of the paper, linear and nonlinear multivariable controllers are designed for the air stream and hydrogen flow with recirculation in a proton exchange membrane (PEM) fuel cell system. The focus of the model is to obtain the desired transient performance of air stoichiometric ratio, cathode inlet pressure, and pressure difference between the anode and the cathode. Based on linearization of the nonlinear dynamic model in the first part of this paper, the coupling between control inputs and performance is analyzed first. The phase relationship between the stack voltage and water transport in frequency domain is meaningful to the future humidity estimation and active purge operation. Then, linear quadratic Gaussian (LQG) algorithm based on observer feedback is used for set-point tracking, and a model-predictive controller (MPC) with an on-line neural network identifier is also designed to improve robustness. Compared with decentralized PI controllers, the multivariable controllers improve the transient response and shows better disturbance rejection capability.
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