基于事件触发机制的离散时变时滞多智能体一致性研究  被引量:1

Study on consensus of discrete multi-agents with time-varying delays based on event-triggered mechanism

在线阅读下载全文

作  者:雷琪[1] 文安格 LEI Qi;WEN Ange(School of Automation,Central South University,Changsha 410083,China)

机构地区:[1]中南大学自动化学院,湖南长沙410083

出  处:《中南大学学报(自然科学版)》2023年第7期2705-2717,共13页Journal of Central South University:Science and Technology

基  金:国家自然科学基金资助项目(62133016)。

摘  要:为降低资源的消耗和浪费,并处理时变时滞对于多智能体的影响,针对离散线性时变时滞多智能体系统,提出一种基于事件触发机制的一致性协议,以减少系统的通信次数。在事件触发机制的框架下,提出一种基于预测控制的分段时滞补偿方法来补偿时变时滞对多智能体系统一致性的影响。在此基础上,通过构造基于延迟划分的Lyapunov-Krasovskii函数分析离散线性多智能系统的稳定性。最后,通过MATLAB仿真验证所提方法的有效性。研究结果表明:事件触发机制可以有效减少系统更新次数,降低消耗,所提出的基于预测控制的分段时滞补偿方法可以弥补时变时滞对于多智能体系统的影响,且基于延迟划分的分段补偿能够降低系统的保守性。In order to reduce the consumption and waste of resources and deal with the influence of time-varying delay on multi-agent systems,a consensus protocol based on event triggered mechanism was proposed to reduce the communication times of discrete linear time-varying delay multi-agent systems.In the framework of event triggered mechanism,a piecewise delay compensation method based on predictive control was proposed to compensate for the influence of time-varying delay on the consensus of multi-agent systems.Then,the stability of discrete linear multi-agent system was analyzed by constructing Lyapunov-Krasovskii function based on delay partition.Finally,the effectiveness of the proposed method was verified by MATLAB simulation.The results show that the event-triggered mechanism can effectively reduce the update times and consumption of the system,the proposed piecewise delay compensation method based on predictive control can compensate for the influence of time-varying delay on the multi-agent system,and the piecewise delay compensation method based on delay partition can reduce the conservatism of the system.

关 键 词:离散线性多智能系统 时变时滞 预测控制 事件触发 

分 类 号:TP273[自动化与计算机技术—检测技术与自动化装置]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象