Balance Control of Brushless Direct Current Motor Driven Two-Rotor UAV

In this study, the balance control of a Brushless Direct Current Motor (BLDCM) driven Two-Rotor UAV (2R-UAV) was carried out. First, a MATLAB/Simulink model of the balance system of the 2R-UAV was built. Afterwards, classical and 2-DOF PID, and proposed Adaptive Fuzzy (AF) 2-DOF PID control structures were created on the STM32F4 microprocessor for both balance angle of the system and speed control of the BLDCMs. Classical and 2-DOF PID controller parameters were determined via Particle Swarm Optimization (PSO), a technique that is commonly used in control applications. For the balance control of the 2R-UAV, a Co-Simulation structure was created using the STM32F4 microprocessor and MATLAB/Simulink, and the performances of classical and 2-DOF PID, and AF 2-DOF PID controllers were examined comparatively. Upon examining the comparison results, it was found that the classical and 2-DOF PID, and AF 2-DOF PID stably controlled the balance of the 2R-UAV. The AF 2-DOF PID controller, proposed in this research, performed better than the classical and 2-DOF PID, especially under variable operating conditions.