This paper addresses the problem of controlling multiple unmanned aerial vehicles (UAVs) cooperating in a formation to carry out a complex task such as surface inspection. We first use the virtual leader-follower model to determine the topology and trajectory of the formation. A double-loop control system combining backstepping and sliding mode control techniques is then designed for the UAVs to track the trajectory. A radial basis function neural network (RBFNN) capable of estimating external disturbances is developed to enhance the robustness of the controller. The stability of the controller is proven by using the Lyapunov theorem. A number of comparisons and software-in-the-loop (SIL) tests have been conducted to evaluate the performance of the proposed controller. The results show that our controller not only outperforms other state-of-the-art controllers but is also sufficient for complex tasks of UAVs such as collecting surface data for inspection. The source code of our controller can be found at https://github.com/duynamrcv/rbf_bsmc

翻译：本文研究了多架无人机协同编队执行复杂任务（如表面检测）的控制问题。首先采用虚拟领航-跟随模型确定编队拓扑结构与轨迹，随后设计了一种结合反步法与滑模控制技术的双环控制系统，使无人机能够跟踪该轨迹。为增强控制器鲁棒性，开发了一种能够估计外部扰动的径向基函数神经网络（RBFNN）。通过李雅普诺夫定理证明了控制器的稳定性。通过多项对比实验及软件在环（SIL）测试对所提控制器的性能进行了评估。结果表明，本文控制器不仅优于其他前沿控制器，而且足以胜任无人机执行表面数据采集等复杂任务。本控制器的源代码可于 https://github.com/duynamrcv/rbf_bsmc 获取。