Liu Shangkun, Jiang Bin, Mao Zehui, Zhang Youmin
IEEE Trans Neural Netw Learn Syst. 2024 May;35(5):6273-6285. doi: 10.1109/TNNLS.2023.3282234. Epub 2024 May 2.
In this article, the issue of adaptive fault-tolerant cooperative control is addressed for heterogeneous multiple unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults and sensor faults under denial-of-service (DoS) attacks. First, a unified control model with actuator faults and sensor faults is developed based on the dynamic models of the UAVs and UGVs. To handle the difficulty introduced by the nonlinear term, a neural-network-based switching-type observer is established to obtain the unmeasured state variables when DoS attacks are active. Then, the fault-tolerant cooperative control scheme is presented by utilizing an adaptive backstepping control algorithm under DoS attacks. According to Lyapunov stability theory and improved average dwell time method by integrating the duration and frequency characteristics of DoS attacks, the stability of the closed-loop system is proved. In addition, all vehicles can track their individual references, while the synchronized tracking errors among vehicles are uniformly ultimately bounded. Finally, simulation studies are given to demonstrate the effectiveness of the proposed method.
本文针对存在执行器故障和传感器故障且遭受拒绝服务（DoS）攻击的异构多无人机（UAV）和无人地面车辆（UGV），研究了自适应容错协同控制问题。首先，基于无人机和无人地面车辆的动力学模型，建立了包含执行器故障和传感器故障的统一控制模型。为解决非线性项带来的困难，建立了一种基于神经网络的切换型观测器，用于在DoS攻击发生时获取不可测状态变量。然后，利用自适应反步控制算法提出了DoS攻击下的容错协同控制方案。根据李雅普诺夫稳定性理论和通过整合DoS攻击的持续时间和频率特性改进的平均驻留时间方法，证明了闭环系统的稳定性。此外，所有车辆能够跟踪各自的参考轨迹，同时车辆间的同步跟踪误差一致最终有界。最后，通过仿真研究验证了所提方法的有效性。
