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带噪音的多智能体系统事件触发有限时间一致性问题

发布时间:2018-05-31 06:19

  本文选题:有限时间一致性 + 事件触发机制 ; 参考:《郑州大学》2017年硕士论文


【摘要】:本文研究了带噪音的多智能体系统的有限时间一致性问题.在固定拓扑下,我们提出一种新颖的基于事件触发机制的的非线性控制策略,控制器和触发机制的设计都是分布式的,他们都仅仅依赖于当前智能体的邻居信息.这种控制策略显著的降低了控制器的更新频率,从而达到极大的减少通讯资源消耗的目的.文章利用代数图论、Ito公式,借助随机Lyapunov控制理论证明了在这种基于事件触发机制的控制策略下,固定拓扑下的带噪音的多智能体系统能够在有限时间达到一致.随后,文章又把该控制策略推广到切换拓扑结构下的多智能体系统,并证明了此控制策略能够使切换拓扑结构下的带噪音的多智能体系统在有限时间能达到一致.文章还给出了一些仿真实例来证实我们所提出的控制策略的合理性以及优越性.
[Abstract]:In this paper, the problem of finite time consistency for multi-agent systems with noise is studied. Under the fixed topology, we propose a novel nonlinear control strategy based on event triggering mechanism. The controller and trigger mechanism are distributed, and they are only dependent on the neighbor information of the current agent. This control strategy significantly reduces the update frequency of the controller, thus greatly reducing the consumption of communication resources. In this paper, by using algebraic graph theory and stochastic Lyapunov control theory, it is proved that under the control strategy based on event triggering mechanism, the multi-agent system with noise under fixed topology can achieve consistency in finite time. Then, the control strategy is extended to the multi-agent system with switching topology, and it is proved that the control strategy can make the multi-agent system with noise under the switching topology consistent in finite time. Some simulation examples are given to verify the rationality and superiority of the proposed control strategy.
【学位授予单位】:郑州大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:O231

【参考文献】

相关期刊论文 前3条

1 Zhongxin LIU;Zengqiang CHEN;Zhuzhi YUAN;;EVENT-TRIGGERED AVERAGE-CONSENSUS OF MULTI-AGENT SYSTEMS WITH WEIGHTED AND DIRECT TOPOLOGY[J];Journal of Systems Science & Complexity;2012年05期

2 ;DISTRIBUTED FINITE-TIME χ-CONSENSUS ALGORITHMS FOR MULTI-AGENT SYSTEMS WITH VARIABLE COUPLING TOPOLOGY[J];Journal of Systems Science & Complexity;2010年02期

3 ;CONSENSUS CONTROL FOR LEADER-FOLLOWING MULTI-AGENT SYSTEMS WITH MEASUREMENT NOISES[J];Journal of Systems Science & Complexity;2010年01期



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