An image-based decoupling controller of quadrotor for moving target tracking

Different from the traditional controller system for quadrotor tasks, the vision-based strategies are more practical and powerful to execute more complex tasks, becoming more attractive to researchers. In this paper, an image-feature-based controller with states extracted in images directly is proposed for the quadrotor to track a moving underground target, in which suitable image features are defined and a coupling problem between position and attitude loop is solved by a decoupling algorithm. Moreover, the external disturbances caused by visual noise, wind, or other problems are eliminated by a robust observer with low-pass filters. A Lyapunov-based stability method is presented to prove the convergent properties of the system. Finally, a simulation using python3.6 with realistic images is established to verify that the system is stable and with high performance, the results of which show the data of unmanned aerial vehicle in moving target tracking.