<p>This paper introduces an optimal fault-tolerant adaptive fuzzy control approach for quadrotor unmanned aerial vehicles (UAVs). The proposed control framework addresses the challenges of unknown nonlinear dynamics, sensor and actuator faults, as well as external disturbances affecting the drone during flight trajectory tracking. For this purpose, a robust control law was developed by combining the backstepping technique, fixed-time stability approach, and fuzzy logic theory. The objective is to achieve rapid compensation for disturbances and faults to prevent stabilization issues and ensure the quick recovery of the UAV. First, the nonlinear dynamic functions and faults are estimated by an adaptive fuzzy system, which is updated online using output variable measurements to guarantee both robustness and performance of closed-loop system. Then, the tuning parameters are automatically selected using the metaheuristic whale optimization algorithm (WOA) to achieve optimal behavior of the drone. The obtained simulation results demonstrate the effectiveness of the proposed controller and highlight its potential for reliable real-world UAV applications.</p>