Catapult take off control based on model predictive control

After separating from the catapult and leaving the flight deck，carrier-based aircraft face multiple constraints including sink rate，angle of attack，and pitch rate to ensure flight safety and quality. Traditional angle-of-attack protection control methods tend to be overly conservative when the attack angle approaches to the stall attack angle，the control system automatically lowers the aircraft's attitude to reduce the angle of attack. While effective in preventing stall，this approach sacrifices partial lift，which is crucial for maintaining sufficient lift during the critical launch phase. To address these issues，a model predictive controller is designed that converts key performance metrics during catapult-assisted takeoff into linear matrix inequality（LMI）constraints. Through online receding horizon optimization，predictive feedback control laws are solved to guarantee asymptotic stability and robustness of the closed-loop system，enabling the aircraft to maintain maximum allowable angle of attack and sustain high-lift flight during the launch phase. The nonlinear simulation cases are validated. The results show that the proposed control method based in LMI constraints and model prediction can realize the sustained high lift flight of carrier based aircraft under multiple constraints during the catapult takeoff phase.