Analytical Study of Metaheuristic Algorithms on Optimization of Contorollers in Quadrotor Drones

Quadrotor is a flying robot with six degrees of freedom which can do vertical flight and complex maneuvers. Since the robot has nonlinear and coupled dynamic model, designing a controller with desired performance involves a large number of interdependent design parameters. The application of meta-heuristic algorithms for PID controller design and adjusting the gain values of the controller is presented in the paper. Therefor three meta-heuristic algorithms have been used for optimal tuning of PID parameters. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Harmony Search (HS) are compared in minimizing the performance criteria formula that can result a better performance for controlling of quadrotor. Finally the PSO algorithm could reduce the cost function more than other evolutionary algorithms and provides suitable answers. To study the performance of PID controller on attitude control of the system, a quadrotor is installed to the designed stand. The system consists of accelerometer and gyroscope sensors and a microcontroller which is used to design PID attitude controller for the quadrotor. Considering that the experimental data has lots of errors and noises, Kalman filter is used to reduce the noises. Finally using the Kalman filter leads to better estimation of the quadrotor angle position and the PID controller performs the desired motions successfully.