Optimal Load Tracking Design for a Catalytic-Partial-Oxidation-Based Fuel Processing System

Abstract

This report presents an optimal control system design for a fuel processing system (FPS) using a generalized linear quadratic Gaussian and loop transfer recovery (LQG/LTR) method. The FPS uses natural gas as fuel and works with a catalytic partial oxidation (CPO) reaction. The control objective focuses on the regulation performances of an output vector in response to a stack current command. First, an optimal controller was designed subject to a generalized linear quadratic performance index to shape the target feedback loop function. Then a Kalman filter was designed to provide an optimal estimation of state variables for minimum and non-minimum phase plants in an LTR process. The proposed method provides another degree-of-freedom in optimal controller design and enables the compensated system to maintain a prescribed degree of stability. Finally, numerical simulations reveal that the proposed method achieves better performance and robustness properties in time- and frequency-domain responses.