Quadcopters Control Using Online Dynamic Mode Decomposition

Abstract

Over the past few years, unmanned aerial vehicles (UAVs) have gained popularity in a wide range of applications such as delivery services, inspection, and monitoring. However, for these applications to be safe and efficient, an accurate model of the UAV's dynamic is essential. In this article, the authors propose a novel control system for the DJI Matrice 100 quadcopter based on the online dynamic mode decomposition with control (DMDc) algorithm and iterative optimal estimation techniques. The online DMDc algorithm enables the identification of the system's dynamic, a critical requirement for an adaptive control. By decomposing the quadcopter's system into dynamic modes, the authors create a precise model of the system's behavior using a Hardware in the Loop (HiL) framework, which is used to design the control system based on inverse dynamics. The adaptive control system can adjust its parameters based on changes in the system's behavior, making it suitable for UAV operations in unpredictable environments. These results demonstrate that the proposed control system significantly improves performance in the presence of disturbances.The research contributes to the field of UAV control and highlights the potential of DMD and adaptive control techniques for enhancing the safety and efficiency of UAV operations.