Model Reference Adaptive Gain-Scheduled PID control for Robust Heading Stabilization in UAM under Wind Disturbances

Urban Air Mobility (UAM) vehicles are poised to revolutionize low-altitude aerial transport. However, maintaining heading stability in the presence of unpredictable and varying wind disturbances remains a significant challenge. This paper proposes a novel model reference adaptive gain-scheduled PID (Proportional-Integral-Derivative) control framework tailored for the heading control of UAMs operating under dynamic wind conditions. The control architecture integrates a real-time wind disturbance observer and adaptively tunes the PID gains by minimizing the error between the actual system response and a desired reference model. A structured gain scheduling mechanism is embedded using flight condition variables such as airspeed, yaw rate, and estimated wind magnitude to ensure stability across a wide operating envelope. In addition, the study highlights the interplay between heading dynamics and the Environmental Control System (ECS), particularly air and thermal management subsystems. These subsystems influence internal cabin pressure, cooling airflows, and thermal loading on avionics, which in turn affect aerodynamic performance and energy consumption. By accounting for these coupled effects, the proposed framework ensures that heading stability is preserved not only under external wind disturbances but also in scenarios where ECS variations induce secondary dynamic loads. The adaptive laws governing gain adjustment are designed for real-time implementation without relying on fixed stability margins, thereby enabling robustness against uncertainty. The proposed method is validated on a high-fidelity 6-DOF UAM simulation model subjected to dynamic wind and ECS-induced variations. Comparative results show improved heading accuracy, responsiveness, and robustness over conventional fixed-gain and static gain-scheduled PID controllers, enhancing safety and reliability in complex urban environments. Keywords: UAM, Model Reference Adaptive Control (MRAC), wind disturbance, PID