Advancing quadcopter autonomy: Comparative analysis of conventional control strategies and integration of fuzzy PID for enhanced performance

The development and utilization of Unmanned Aerial Vehicles (UAVs) continue to grow, it becomes increasingly important to address the challenges related to their control and performance. UAVS performance is completely dependent on their control system be- havior. In this master's project the main objective lies to study those different controllers when the model is against disturbance and uncertainties, comparing and analyzing the proposed three conventional control strategies: (a proportional integral derivative (PID) controller, a Backstepping controller and a fuzzy pid controller ) and all that to regulate and control the behavior and stability of quadcopter UAVs. To achieve these objec- tives, a comprehensive methodology is outlined encompassing comprehensive approach for dynamic modeling, control system design,Parameter Tuning,performance evaluation, simulation of a quadcopter with analysing it's results. Utilizing careful adjustments and fine-tuning, each control strategy is customized to attain the desired dynamic response and stability during quadcopter flight. Furthermore, this thesis seeks to explore the fuzzy logic into the PID control combination framework to create a hybrid control strategy, termed the Fuzzy PID controller. Leveraging MATLAB as a powerful tool, the quadcopter is empowered to autonomously navigate complex en- vironments.Extensive simulation experiments and evaluations, conducted in MATLAB, precisely compare the performance of the different control strategies and it showed promis- ing responses to the tests carried out. The results indicated the limits of the PID controller but it's effectiveness after combining it with fuzzy logic. Overall, this research significantly advances the field of quadcopter control and autonomy, presenting valuable insights and solutions for optimizing flight stability and enabling secure