Optimal control design of fuel processing system by linear quadratic Gaussian and loop transfer recovery method

This paper presents an optimal control system which consists of both feedforward and state-feedback controllers designed using a well-developed linear quadratic Gaussian and loop transfer recovery (LQG/LTR) method for a fuel processing system (FPS). This FPS uses natural gas as fuel and reacts with atmospheric air through a catalytic partial oxidation (CPO) response. The control objective is focused on the regulatory performance of output vector in response to a desired stack current command in face of load variation. First, a Kalman filter is designed to provide an optimal estimation of state variables and to shape the target feedback loop function. And then an optimal two-degree-of-freedom controller is designed subject to a linear quadratic performance index in the LTR process. Finally, the numerical simulations of compensated FPS reveal that theproposed method achieves better performance and robustness properties than presently accepted methods, in both time-domain and frequency-domain responses.