Model Reference Adaptive Control (MRAC) for Drone

Drone motor failure poses a critical safety risk, and adaptive control strategies offer a promising path toward fault-tolerant flight. This project implements Model Reference Adaptive Control (MRAC) in Python and Webots to compare its performance against a standalone LQR controller under a simulated quadrotor motor failure scenario, with MRAC successfully stabilizing flight at up to 70% motor failure where LQR alone could not.