Abstract
This paper studies the leader-following consensuses of uncertain and nonlinear multi-agent systems against composite attacks (CAs), including Denial of Service (DoS) attacks and actuation attacks (AAs). A double-layer control framework is formulated, where a digital twin layer (TL) is added beside the traditional cyber-physical layer (CPL), inspired by the recent Digital Twin technology. Consequently, the resilient control task against CAs can be divided into two parts: One is distributed estimation against DoS attacks on the TL and the other is resilient decentralized tracking control against actuation attacks on the CPL. %The data-driven scheme is used to deal with both model non-linearity and model uncertainty, in which only the input and output data of the system are employed throughout the whole control process. First, a distributed observer based on switching estimation law against DoS is designed on TL. Second, a distributed model free adaptive control (DMFAC) protocol based on attack compensation against AAs is designed on CPL. Moreover, the uniformly ultimately bounded convergence of consensus error of the proposed double-layer DMFAC algorithm is strictly proved. Finally, the simulation verifies the effectiveness of the resilient double-layer control scheme.
Abstract (translated)
本论文研究的是不确定和非非线性多Agent系统的领袖跟随共识，包括拒绝服务(DoS)攻击和操纵攻击(AAs)。提出了一种双重控制框架，在该框架中，数字孪层(TL)被添加到传统的网络物理层(CPL)的旁边，以借鉴最近的数字孪技术。因此，对CAs的 resilient控制任务可以分成两个部分：第一部分是针对TL的DoS攻击分布式估计，第二部分是针对 CPL的操纵攻击 resilient分布式跟踪控制。采用数据驱动的方法处理模型非线性和模型不确定性，在整个控制过程中仅使用系统的输入和输出数据。首先，在 TL 上设计了一个基于切换估计 law 的分布式观察者。其次，在 CPL 上设计了一个基于攻击补偿对 AAs 的分布式模型自由自适应控制(DMFAC)协议。此外，非常严格证明了所提出的双层 DMFAC 算法的共识误差uniformly最终限定的收敛。最后，仿真验证了 resilient 双层控制框架的有效性。
URL
https://arxiv.org/abs/2303.12823
