A Scheduling Scheme of Linear Model Predictive Controllers for Turbofan Engines

An adaptive model predictive controller with a new scheduling scheme for turbofan engines is proposed, which can transfer engine from one working state to the others within the flight envelope. First, the flight envelope is divided into several sections according to the engine inlet parameters, and the nominal points in each section are determined, respectively. Then, considering the requirements of the turbofan engines, a constrained linear model predictive control algorithm is improved, and a series of constrained predictive controllers are designed based on the linear models at different nominal points. Furthermore, a novel scheduling scheme with two layers is constructed, where the first layer is the flight envelope scheduling layer that introduces fuzzy membership degree logic to distribute the weights of all nominal predictive controllers, and the second layer is the power scheduling layer by adopting a linear interpolation method. Simulation results show that the proposed scheduling scheme can coordinate these two layers to realize the steady-state and transition-state control of the turbofan engines at off-nominal points within the envelope, which provides an effective approach for the design of the adaptive controllers.