Adaptive Robust Control of the UAV-USV Heterogeneous System with Unknown Fractional-Order Dynamics under Multiple Disturbances
Zixuan Liu, Dongyue Huang, Shengquan Li, Weidong Zhang, Haibo Lu
- Year
- 2023
- Citations
- 4
Abstract
This paper addresses the robust formation tracking problem for a heterogeneous multi-robot system consisting of unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). When performing complex marine missions involved with the oil spills, such as oil spill cleanup tasks or marine search and rescue tasks, the USV in the marine multi-robot system will become a fractional-order system with uncertain dynamics and the UAV will be affected by multiple dynamic disturbances. This work proposed a distributed formation control scheme for the UAVs to track the fractional-order USV while maintaining a desired heterogeneous formation. Radial Basis Function Neural Network (RBFNN) is used in the design of the controller for the UAVs to approximate the uncertain dynamics of the USV. The estimation and compensation of the multiple disturbances of each UAV are handled by the Uncertainty Disturbance Estimator (UDE) method. Then, the stability of the distributed control law for the heterogeneous multi-robot system was mathematically proved based on a Lyapunov function term. A simulation case study with four UAVs and a USV was conducted to validate the effectiveness of the proposed control scheme and the results have successfully demonstrated the robustness of the formation tracking control strategy.
Keywords
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