Robust Consensus of Nonlinear Multiagent Systems With Switching Topology and Bounded Noises
研究了在切换拓扑和有界噪声环境下，非线性多智能体系统如何实现鲁棒一致性，通过非光滑李雅普诺夫方法证明了条件，并用仿真验证了有效性。
Consensus of multiagent systems (MASs) is an intriguing topic in recent years due to its widely used application in robotics, biology, computer, and social science. In the real world, the evolution of MAS is inevitably involved in dynamical environments and the recent development of MAS calls for novel tools for the analysis of MAS with dynamic topology. In addition, the interactions between agents are generally nonlinear and environmental noises are ubiquitous in the communication channels between agents. However, the existing investigation on MAS places little attention on nonlinear models and the inner relationship between external disturbance and consensus is still unclear. Facing these problems, this paper considers an MAS in which the interactions between agents are nonlinear and the communication between agents are infected by environmental noises. By using a novel method of nonsmooth Lyapunov candidate, it has been demonstrated that such an MAS can realize robust consensus under the conditions of jointly (sequentially) connected topology and bounded noises. Finally, simulation results validate the effectiveness of these criteria.