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基于线性变换的领导-跟随多智能体系统动态反馈均方一致性控制

郑维 张志明 刘和鑫 张明泉 孙富春

郑维, 张志明, 刘和鑫, 张明泉, 孙富春. 基于线性变换的领导-跟随多智能体系统动态反馈均方一致性控制. 自动化学报, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200850
引用本文: 郑维, 张志明, 刘和鑫, 张明泉, 孙富春. 基于线性变换的领导-跟随多智能体系统动态反馈均方一致性控制. 自动化学报, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200850
Zheng Wei, Zhang Zhi-Ming, Liu He-Xin, Zhang Ming-Quan, Sun Fu-Chun. Dynamic feedback mean square consensus control based on linear transformation for leader-follower multi-agent systems. Acta Automatica Sinica, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200850
Citation: Zheng Wei, Zhang Zhi-Ming, Liu He-Xin, Zhang Ming-Quan, Sun Fu-Chun. Dynamic feedback mean square consensus control based on linear transformation for leader-follower multi-agent systems. Acta Automatica Sinica, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200850

基于线性变换的领导-跟随多智能体系统动态反馈均方一致性控制

doi: 10.16383/j.aas.c200850
基金项目: 河北省教育厅高等学校科技计划自然科学基金(QN2021138), 河北省自然科学基金(F2016203496)
详细信息
    作者简介:

    郑维:燕山大学电气工程学院讲师. 主要研究方向为非线性系统控制, 多机器人协同控制, 多智能体编队. E-mail: weizheng@stumail.ysu.edu.cn

    张志明:燕山大学电气工程学院, 在读博士研究生. 主要研究方向为自适应学习系统, 非线性控. 本文通信作者. E-mail: zhangzhiming0925@163.com

    刘和鑫:东北大学信息科学与工程学院研究生, 主要研究方向为区间神经网络建模, 不确定系统鲁棒控制等. E-mail: 18842422709@163.com

    张明泉:燕山大学电气工程学院, 在读硕士研究生. 主要研究方向为非线性控制和优化. E-mail: xiaoxiongvivian@126.com

    孙富春:清华大学信息科学技术学院教授. 主要研究方向为智能控制, 机器人与飞行器的导航与控制. E-mail: fcsun@tsinghua.edu.cn

Dynamic Feedback Mean Square Consensus Control Based on Linear Transformation for Leader-Follower Multi-Agent Systems

Funds: Supported by Natural Science Foundation for High Education College Science and Technology Plan of Hebei Province (QN2021138), Natural Science Foundation of Hebei Province (F2016203496)
More Information
    Author Bio:

    ZHENG Wei Lecturer at the School of Electrical Engineering, Yanshan University. His research interest covers nonlinear systems control, multi robot cooperative control, and multi-agent formation

    ZHANG Zhi-Ming Ph. D. Student at the School of Electrical Engineering, Yanshan University. His research interest covers adaptive and learning systems, nonlinear control and optimization. Corresponding author of this paper

    LIU He-Xin Master Student at the School of information science and Engineering, Northeastern University. His research interest covers interval neural network modeling, robust control of uncertain systems and multi robot cooperative control

    ZHANG Ming-Quan Master Student at the School of Electrical Engineering, Yanshan University. His research interest covers nonlinear control and optimization, deep learning control and application in robots

    SUN Fu-Chun Professor at the School of Information Science and Technology, Tsinghua University. His research interest covers Intelligent control, navigation and control of robot and aircraft

  • 摘要: 本文研究了基于半马尔科夫(Markov)跳变的领导-跟随多智能体系统的均方一致性控制问题. 首先, 针对多智能体系统同时存在通信时滞和执行器故障的问题, 提出基于线性变换的动态反馈控制策略. 其次, 将实现领导-跟随多智能体系统的均方一致性问题转化为多智能体误差系统的稳定性控制问题. 再次, 设计动态反馈控制器, 利用李亚谱诺夫(Lyapunov)函数抑制系统的非线性特性, 解决由控制器未知增益矩阵产生的非线性问题. 使领导-跟随多智能体系统达到均方一致, 并给出系统的${H_{\infty} }$性能指标分析系统的鲁棒性. 最后, 仿真结果表明基于线性变换设计的动态反馈控制策略具有良好的控制性能, 并且能够提高领导-跟随多智能体系统的动态特性.
  • 图  1  系统通信拓扑结构

    Fig.  1  The topological structure of system communication

    图  2  状态变量${{{x}}_{i1}}\left( t \right)$响应曲线

    Fig.  2  The response of state variable ${{{x}}_{i1}}\left( t \right)$

    图  3  状态变量${{{x}}_{i2}}\left( t \right)$响应曲线

    Fig.  3  The response of state variable ${{{x}}_{i2}}\left( t \right)$

    图  4  系统误差$e\left( t \right)$响应曲线

    Fig.  4  The response of system error $e\left( t \right)$

    图  5  通信拓扑切换信号

    Fig.  5  The switching signal of communication topology

    图  6  系统通信拓扑结构

    Fig.  6  The topological structure of system communication

    图  7  状态变量${{{x}}_{i1}}\left( t \right)$响应曲线

    Fig.  7  The response of state variable ${{{x}}_{i1}}\left( t \right)$

    图  8  状态变量${{{x}}_{i2}}\left( t \right)$响应曲线

    Fig.  8  The response of state variable ${{{x}}_{i2}}\left( t \right)$

    图  9  系统误差$e\left( t \right)$响应曲线

    Fig.  9  The response of system error $e\left( t \right)$

    图  10  通信拓扑切换信号

    表  1  ${\tau _M}$取不同值时$\gamma $对比结果

    Table  1  Comparison results of $\gamma $ with different ${\tau _M}$

    方法 ${\tau _M}$
    0.400.450.500.550.60
    [37]0.52470.54700.56240.58850.6075
    定理20.50500.52340.54750.56690.5849
    下载: 导出CSV

    表  2  ${\tau _M}$取不同值时$\gamma $对比结果

    Table  2  11:erhhz with different ${\tau _M}$

    方法 ${\tau _M}$
    0.650.700.750.800.85
    [37]0.62760.64720.66030.68180.7022
    定理20.60060.62540.64190.66570.6895
    下载: 导出CSV
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  • 收稿日期:  2020-10-14
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