Quaternion-based optimal control for PX4 hardware-in-the-loop drone systems

This thesis focuses on the development and implementation of an optimal control strategy for quadrotor drones using quaternion-based representations and on the architecture of Hardware-In-The-Loop (HITL) simulations. A detailed dynamic model of a quadrotor is derived, highlighting the advantages of using quaternions for attitude representation to eliminate singularities. A quaternion-based differential calculus framework is introduced to handle optimization problems involving quaternions effectively. The trajectory optimization process is adapted to the quaternion framework, ensuring consistency with the drone dynamics. A finite-horizon LQR controller is then designed to track the computed trajectory. The proposed control strategy is validated through both Software-In-The-Loop (SITL) and Hardware-In-The-Loop (HITL) simulations using the PX4-Autopilot framework. The SITL simulations demonstrate the controller ability to achieve precise trajectory tracking under ideal conditions, while the HITL simulations highlight the controller robustness in a more realistic environment, accounting for sensor noise and hardware limitations. The results confirm the effectiveness of the quaternion-based optimal control approach in achieving accurate and stable flight performance.