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有向图中网络Euler-Lagrange系统无需相对速度信息的群一致性

曹然 梅杰

曹然, 梅杰. 有向图中网络Euler-Lagrange系统无需相对速度信息的群一致性. 自动化学报, 2018, 44(1): 44-51. doi: 10.16383/j.aas.2018.c160637
引用本文: 曹然, 梅杰. 有向图中网络Euler-Lagrange系统无需相对速度信息的群一致性. 自动化学报, 2018, 44(1): 44-51. doi: 10.16383/j.aas.2018.c160637
CAO Ran, MEI Jie. Group Consensus for Networked Euler-Lagrangian Systems Under a Directed Graph Without Relative Velocity Information. ACTA AUTOMATICA SINICA, 2018, 44(1): 44-51. doi: 10.16383/j.aas.2018.c160637
Citation: CAO Ran, MEI Jie. Group Consensus for Networked Euler-Lagrangian Systems Under a Directed Graph Without Relative Velocity Information. ACTA AUTOMATICA SINICA, 2018, 44(1): 44-51. doi: 10.16383/j.aas.2018.c160637

有向图中网络Euler-Lagrange系统无需相对速度信息的群一致性

doi: 10.16383/j.aas.2018.c160637
基金项目: 

深圳市基础研究计划 JCYJ20160505175231531

国家自然科学基金 61403094

详细信息
    作者简介:

    曹然哈尔滨工业大学(深圳)机电工程与自动化学院硕士研究生.2015年获得哈尔滨工程大学自动化专业学士学位.主要研究方向为非线性多智能体系统的协调控制.E-mail:crhgc2011@hotmail.com

    通讯作者:

    梅杰哈尔滨工业大学(深圳)机电工程与自动化学院副教授.主要研究方向为多智能体系统分布式控制及其在编队飞行器中的应用.本文通信作者.E-mail:jmei@hitsz.edu.cn

Group Consensus for Networked Euler-Lagrangian Systems Under a Directed Graph Without Relative Velocity Information

Funds: 

the Foundation Research Project of Shenzhen JCYJ20160505175231531

National Natural Science Foundation of China 61403094

More Information
    Author Bio:

    Master student at the School of Mechanical Engineering and Automation, Harbin Institute of Technology (Shenzhen). He received his bachelor degree in automation from Harbin Engineering University in 2015. His research interest covers coordination of nonlinear multi-agent systems

    Corresponding author: MEI Jie Associate professor at the School of Mechanical Engineering and Automation, Harbin Institute of Technology (Shenzhen). His research interest covers distributed control of multi-agent systems and its application in formation flying. Corresponding author of this paper
  • 摘要: 在非对称有向图中,研究网络Euler-Lagrange系统的群一致性问题.每组内的智能体均为合作关系,而组间智能体则可以为合作关系或竞争关系.为了实现群一致性,假设组与组之间是无环连接的且系统有向图满足入度平衡条件.考虑到智能体间相对速度信息难以精确测量的实际情形,设计无需相对速度信息的分布式自适应控制算法,实现网络Euler-Lagrange系统的群一致性.最后通过仿真分析验证所设计算法的有效性.
    1)  本文责任编委 夏元清
  • 图  1  智能体间的拓扑关系

    Fig.  1  The networked topology associated with the agents

    图  2  有向拓扑图下智能体位置状态信息

    Fig.  2  The position state of agents under the directed interaction graph

    图  3  有向拓扑图下智能体速度信息

    Fig.  3  The velocities of agents under the directed interaction graph

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出版历程
  • 收稿日期:  2016-09-06
  • 录用日期:  2017-02-03
  • 刊出日期:  2018-01-01

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