This thesis provides an extensive investigation of quadrotor dynamics control, specifically emphasizing translational and attitude control through the implementation of various advanced techniques. The quadrotor system is represented as a sophisticated multi-input multi-output (MIMO) system, with distinct sets of equations governing the dynamics of translation and attitude. A novel control technique is presented for translational dynamics, incorporating backstepping, region-reaching strategies, and obstacle avoidance. Backstepping is employed to develop a stable control law that ensures convergence to a predefined region in three-dimensional space while avoiding obstacles. The proposed control strategy employs artificial potential functions to guide the quadrotor through a dynamic environment safely. Based on the backstepping method, the region-reaching controller exhibits the capability to accurately follow desired trajectories while effectively avoiding potential obstacles, thereby guaranteeing the safety and dependability of quadrotor navigation. A modified terminal sliding mode control approach is used in attitude dynamics. Integrating a Radial Basis Function (RBF) neural network enhances this technique by effectively handling uncertainties and disturbances. The revised terminal sliding mode controller guarantees the quadrotor’s stable control over its attitude, even when faced with external disturbances and uncertainties in the model. The RBF neural network is employed to adjust the control inputs, allowing the quadrotor to achieve accurate attitude control, which is crucial for tasks such as aerial photography, surveillance, or any other application requiring stable positioning. The simulations are performed utilizing MATLAB/Simulink, which offers a virtual setting for testing and verifying the suggested control methods. The results indicate that the backstepping-based region reaching and modified terminal sliding mode control strategies are effective and robust. This suggests that these strategies have the potential to be applied in real-world quadrotor systems. This study makes a valuable contribution to the progress of quadrotor control systems by introducing novel methods to handle translational and attitude dynamics. The research places a significant focus on ensuring safety and achieving high levels of accuracy.