A Novel Bipartite Consensus Tracking Control for Multiagent Systems Under Sensor Deception Attacks
提出一种基于最短路径技术的自适应二分一致性跟踪策略，通过动态估计器应对传感器欺骗攻击，避免现有方法的迭代奇异性，并利用Nussbaum函数处理未知控制增益。
This article presents a novel adaptive bipartite consensus tracking strategy for multiagent systems (MASs) under sensor deception attacks. The fundamental design philosophy is to develop a hierarchical algorithm based on shortest route technology that recasts the bipartite consensus tracking problem for MASs into the tracking problem for a single agent and eliminates the need for any global information of the Laplacian matrix. As the sensors suffer from malicious deception attacks, the states cannot be measured accurately, we thus construct a novel dynamic estimator to estimate the actual states, which, together with a new coordinate transformation involving the attacked and estimated state variables, allows a distributed security control scheme to be developed, in which the singularity of the adaptive iterative process involved in existing works is completely avoided. Furthermore, the Nussbaum functions are included in the controller to account for the influence of the unknown control gains caused by sensor deception attacks. It is shown that the distributed consensus tracking errors converge to a small neighborhood of the origin, and all the signals in the closed-loop system remain bounded. Simulation on a forced damped pendulums (FDPs) is conducted to demonstrate and verify the effectiveness of the proposed strategy.