Energy-based nonlinear adaptive control for collaborative transportation systems


As an ideal method for heavy or large payload delivery, collaborative aerial transportation with multiple unmanned aerial vehicles (UAVs) increases the load capacity. However, during the transportation process, collaborative transportation systems are always subject to environmental disturbances and system uncertainties, which poses a great challenge to safe and efficient payload transportation. Existing works without payload angle information in control inputs cannot exhibit satisfactory antiswing performance. To handle the aforementioned issues, this paper proposes a novel control strategy for rapid UAV positioning and payload swing elimination. Specifically, the dynamic model of the collaborative transportation system is described based on a redundant dynamic expression. Then, an artificially constructed UAV-payload unified signal is introduced to enhance the state coupling between the UAV positions and payload swing angles. Based on the newly defined signal, the energy storage function is constructed and the adaptive control law is derived. Additionally, the detailed Lyapunov analysis is provided to prove the system stability and convergence. It is worth noting that the difficulty of the stability analysis is greatly reduced with the help of the established redundant dynamic description. To validate the performance of the proposed control strategy, experimental studies have been carried out in different scenarios. Hardware experimental results show that the proposed method can effectively suppress load swing while ensuring rapid UAV positioning, even with external disturbances.

» Author: Yi Chai, Xiao Liang, Zhichao Yang, Jianda Han

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


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