Comparison of model predictive controller and min-max approach for aircraft engine fuel control

Aeroengines use a Min-Max selector structure for fuel flow control. This structure should provide desired fan speed command and prevent the engine from violation of physical and operational limits. Recent studies show that there is no guarantee for Min-Max algorithm with linear compensators to protect engine limits during transient state, while limit violation can make dangerous events. In this study, based on a reliable turbofan engine model, a Min-Max selector controller with linear compensators is designed as the traditional controller for gas turbine engines. Then, model predictive control (MPC) technique which can provide optimal control input with regarding input/output constraints is designed as a modern model-based controller. The performance of the Min-Max selector algorithm and model predictive controller are compared in tracking a general fan speed scenario and limit protection. The simulation results show that the MPC method provides faster response and prevent limit violation in compare with Min-Max approach.