Adaptive Fuzzy Logic Control of Quadrotor - Yasmine, Zamoum; Karim, Baiche; Razika, Boushaki; Younes, Benrabah (International Journal of Robotics and Control Systems, 2024)
Intelligent controllers are created in this work to regulate the attitude of quadrotor UAVs (Unmanned Aerial Vehicles). Quadrotors offer a wide range of real-time applications, including surveillance, inspection, search and rescue, and lowering the human force safety risks. The kinematics of quadrotor are similar to those of an inverted pendulum. To maintain balance, they must continuously adjust orientation and thrust. External disturbances, like wind or sudden movements, can easily destabilize them, necessitating sophisticated control algorithms for stable flight and precise maneuverability. This instability poses a significant challenge in designing and operating quadrotors, especially in dynamic environments where real-time adjustments are crucial for maintaining control. To avoid any form of damage, a mathematical model should be constructed first, followed by the implementation of various control systems. A thorough simulation model for a Quadrotor is presented in this project. The quadrotor is a six degrees of freedom object, it has six variables to express its position in space where (x, y and z) represent the distance of quadrotor from an earth fixed inertial form to its center of mass, main movements of roll, pitch, yaw are the Euler angles representing the orientation of the quadrotor at each axis. The proposed control techniques are applied separately: PID Controller, Fuzzy Logic PID Controller and Adaptive Fuzzy Logic PID Controller. The purpose of this work is to asses these control techniques for the motions of a Quadrotor in terms of better performance, tracking error reduction, and stability. MATLAB software is used for modeling, control, and simulation. According to the obtained results, the PID controller provided the best settling time. In addition, when we applied fuzzy logic PID control to adjust the pitch angle, the system experienced overshoot; however, with Adaptive Fuzzy Logic PID controller, the system provided the best performance according to the desired criteria.