Design and Implementation of a Robust 6-DOF Quadrotor Controller Based on Kalman Filter for Position Control

The objective of this chapter is to develop quadcopter flight control algorithms using a PID controller enhanced by a Kalman Filter (KF) using an experimental approach to extract the physical and aerodynamic settings of the quadcopter. It is first necessary to present the current state of the quadcopter analytical dynamics model in order to achieve an effective design. A second step involves the development of the quadcopter’s hardware and software, as well as the development of a full thrust test rig to extract the parameters of the propulsion system and the linearisation approximations between the different variables. Using the quadcopter’s 6-DOF analytical dynamic model, the controller’s control parameters are determined using a PID design enhanced with KF. Test results were assessed using dynamic response curves and 3D Matlab visualisations. In order to evaluate the performance of the PID controllers, we measured the time response, overshoot, and settling time with and without the KF. After the SIMULINK model’s results for the drone were accepted, a C++ code was produced. Uploading the generated code into the Pixhawk autopilot was accomplished through a Simulink application in the autopilot firmware. Based on the Pixhawk autopilot, we present a quick and real-time test solution for drone controllers. Further enhancements are provided by near-real-time tuning of the control settings. This research uses the Embedded Coder Tool to develop SIMULINK-generated code for the Pixhawk autopilot board.