Efficient Tube Model Predictive Control for Safety-Aware Operation of Aero-Engine

Aero-engines directly affect the aircraft’s performance, safety, and reliability, thus playing a vital role in aviation. However, aero-engines operate in tough environments with high temperatures and pressures, which impose system constraints and uncertainties due to environmental variations, such as inlet wind speed, ambient temperature, barometric pressure, and inlet conditions leading to challenging control problems for aero-engines. To cope with these challenges, we develop a robust model-predictive control (RMPC) approach for aero-engine applications in this brief. Furthermore, to address the computational burden in traditional RMPC methods caused by the iterative nature of solving optimization problems, we propose a method called efficient tube MPC (ET-MPC), which ensures efficient computation and reduced computational time through the design of an event-triggered mechanism while guaranteeing adherence to tracking control constraints. The stability and feasibility of the proposed method are demonstrated. Finally, we conducted simulation experiments on a real world aero-engine model to validate the efficiency and safety of the ET-MPC algorithm.