Adaptive Digital PID Control of a Quadcopter with Unknown Dynamics
This work addresses control challenges for quadcopters in applications like drones, but it is incremental as it modifies an existing autopilot architecture.
The paper tackled the problem of controlling a quadcopter with unknown dynamics by developing an adaptive autopilot using retrospective cost adaptive control (RCAC), resulting in successful trajectory following in all test cases with zero initial gains and varied moment-of-inertia.
This paper develops an adaptive autopilot for quadcopters with unknown dynamics. To do this, the PX4 autopilot architecture is modified so that the feedback and feedforward controllers are replaced by adaptive control laws based on retrospective cost adaptive control (RCAC). The present paper provides a numerical investigation of the performance of the adaptive autopilot on a quadcopter with unknown dynamics. In order to reflect the absence of prior modeling information, all of the adaptive digital controllers are initialized at zero gains. In addition, moment-of-inertia of the quadcopter is varied to test the robustness of the adaptive autopilot. In all test cases, the vehicle is commanded to follow a given trajectory, and the resulting performance is examined.