Mathematical Modeling and Analysis of Pid-Based Flight Control Systems for Unmanned Aerial Vehicles
TL;DR
This study presents the mathematical modeling and simulation-based analysis of PIDbased flight control systems for UAV stabilization and discusses the advantages, limitations, and tuning challenges of PID controllers and indicates the future potential of adaptive and AI-based control methods for UAV stabilization.
Abstract
Unmanned aerial vehicles (UAVs) are increasingly used in civilian, industrial, and specialpurpose applications due to their mobility, flexibility, and autonomous operating capabilities. One of the main technical challenges in UAV systems is maintaining stable flight performance under changing operating conditions and external disturbances. Flight stability directly affects navigation accuracy, maneuverability, and overall system reliability. Therefore, automatic flight control systems based on proportional-integral-derivative (PID) controllers remain widely applied in modern UAV platforms. This study presents the mathematical modeling and simulation-based analysis of PIDbased flight control systems for UAV stabilization. The proposed approach focuses on roll, pitch, and yaw attitude control using a classical PID controller structure. The UAV dynamic model, PID control law, and main performance indicators, including overshoot, settling time, rise time, and steady-state error, are analyzed. Simulation results show that properly selected PID parameters significantly improve the dynamic response of the UAV attitude-control system. Compared with low-gain and medium-gain configurations, the optimized PID controller provides faster stabilization, lower steadystate error, and improved response smoothness. The study also discusses the advantages, limitations, and tuning challenges of PID controllers and indicates the future potential of adaptive and AI-based control methods for UAV stabilization.