Nonlinear Model Predictive Control of Urban Air Mobility Aircraft Subject to Stochastic Gust Excitations

Abstract The paper explores improving the ride quality of urban air mobility (UAM) aircraft by using a nonlinear model predictive controller (NMPC) for trajectory tracking in the presence of gusts. A hybrid UAM aircraft with traditional control surfaces and multiple rotors is studied. The aircraft’s free-flight behavior is governed by a set of nonlinear rigid-body dynamic equations that account for the gyroscopic and inertial effects of the tiltrotors. The control inputs for the aircraft include the spin rate and acceleration of the rotors, their tilt angle and rate, and the deflections of traditional control surfaces, such as the elevator, aileron, and rudder. This research numerically studies the effects of NMPC in actively suppressing the dynamic responses of the aircraft to continuous stochastic gusts applied symmetrically and asymmetrically on the lifting surfaces. The findings indicate that NMPC can effectively maintain the aircraft on its desired flight path, closely resembling the undisturbed level flight under moderate-intensity gusts. However, the controller’s effectiveness decreases as gust intensity increases. When the intensity of gusts surpasses a specific threshold, the NMPC is unable to constrain flight path deviation within a bounded range, primarily due to an increased pitch rate. This highlights the limitations of NMPC under extreme gust conditions, while demonstrating its effectiveness in managing moderate gust scenarios.