李普希茨连续性
共识
计算机科学
控制器(灌溉)
控制理论(社会学)
芝诺悖论
凸函数
最优化问题
数学优化
凸优化
功能(生物学)
分布式计算
多智能体系统
正多边形
数学
控制(管理)
算法
数学分析
几何学
人工智能
进化生物学
农学
生物
作者
Dandan Wang,Jialing Zhou,Guanghui Wen,Jinhu Lü,Guanrong Chen
标识
DOI:10.1109/tnse.2023.3274559
摘要
This paper investigates the distributed optimal consensus problem (DOCP) for second-order multi-agent systems (MASs) in the presence of system disturbances and cyber attacks on communication edges. In optimization, the global objective function is the sum of a class of local private objective functions, which are assumed to be strongly convex and continuously differentiable with Lipschitz continuous gradients. Unlike most optimization problems for MASs studied in the literature, in this study, the dynamics of agents are second-order and disturbed, considering cyber attacks among neighboring agents. In order to achieve DOC with low online resource consumption, novel distributed event-triggered controllers are designed for agents. Not only the communication and computation resources can be saved, but also the frequency of controller updates can be reduced. Moreover, the controllers can prevent the information of the states of second-order MASs from leaking to neighbors. Under restrictions on cyber attacks, sufficient conditions are derived, under which all controlled agents can achieve consensus on the optimal solution of the global objective function exponentially. Furthermore, the Zeno-behavior is excluded on triggering time sequences. Finally, three simulation examples are shown to illustrate the effectiveness of the designed controllers in saving online resources.
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