植绒(纹理)
控制理论(社会学)
二部图
执行机构
计算机科学
控制(管理)
人工智能
物理
理论计算机科学
图形
量子力学
作者
Jiaqi Lu,Kaiyu Qin,Meng Li,Boxian Lin,Mengji Shi
标识
DOI:10.1016/j.chaos.2024.114556
摘要
Flocking is a remarkable phenomenon observed in self-organization agent groups, where individuals follow simple interaction rules to achieve collective grouping behavior. This paper aims to address the challenge of robust bipartite flocking control for networked agents that are susceptible to actuator attacks and external perturbations. The interactions among the networked agents are represented using a signed network model, which encompasses both attractive and repulsive interactions. To begin with, distinct finite-time and fixed-time bipartite flocking control schemes are formulated, with predetermined upper bounds for the settling time of both schemes. Additionally, a nonlinear component associated with velocity alignment errors is incorporated into the flocking controller to compensate for external disturbances encountered by the agents, thereby enhancing the system's resilience in the face of such disruptions. Furthermore, fault-tolerant finite-time and fixed-time control schemes are proposed for the agents experiencing actuator attacks, enabling the adjustment of settling times based on the actual capabilities of each agent. Finally, the effectiveness of the developed bipartite flocking control schemes for networked agents is demonstrated through some numerical simulation examples.
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