Optimization and Comparative Analysis of 3-DoF Quadcopter Control: PID-GA, LQR, MPC

Nowadays, quadcopters are used in various applications around the world. However, advanced stabilizing control is required to manage the complex nonlinear dynamic behavior of the quadcopter during its movement. This work concentrates on developing an efficient mathematical model to simulate the 3 Degree of Freedom (3DOF) quadcopter's dynamics, allowing for an effective controller design. Moreover, we have designed two controllers for the linearized mathematical model of a 3 DOF quadcopter to achieve the optimal response. First, we developed the PID controller for it. Tuning gains for model-based control is often tedious, so automating PID optimization for the quadcopter can improve performance and reduce manual effort. Therefore, we have optimized the PID controller using Genetic Algorithms (GA). Moreover, LQR and Model Predictive Controller (MPC) are also designed to stabilize the movements of the 3DOF quadcopter. All three controllers are simulated in MATLAB Simulink, where all controllers performed well, but PID-GA and MPC show better results overall.