This work outlines a solid control structure for a quadrotor Unmanned Aerial Vehicle (UAV) using Model Reference Adaptive Control (MRAC) coupled with a Linear Quadratic Regulator (LQR). The control architecture is intended to provide obstacle-free guaranteed operation and stable tracking of desired trajectories while dealing with model uncertainties and actuator faults. Fault tolerant control is implemented in the telemetry system. A detailed nonlinear UAV model encompassing complete translational and rotational dynamics has been developed in MATLAB/Simulink. We study several scenarios including regulation and trajectory tracking tasks which are tested from two different configurations of control setup: Adaptive OFF, which is Baseline Control only, and Adaptive ON, which is Baseline control plus Adaptive Control. Results demonstrated that while the LQR controller was able to perform nominally under expected conditions, did not maintain control, nor did situational tracking accuracy when losing an actuator. In contrast, systems with MRAC showed much better behavior being able to mitigate disturbances while accurately following trajectories under all tested conditions. As verified by Lyapunov theory, the adaptive controller maintains closed-loop stability while dynamically modifying control inputs with feedback from tracking error and regressor. The project illustrates the significance of adaptation for robust UAV control and underscores the merit of model-driven simulations for sophisticated controller validation. This design proposal is aimed at the integration of intelligent fault-tolerant UAV systems into challenging and unpredictable operational scenarios.