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复杂网络的无模型自适应牵制控制

  • 陶昭 ,
  • 侯忠生 ,
  • 陶昭 ,
  • 侯忠生
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  • 青岛大学自动化学院,山东 青岛 266071
陶昭(1997),男,湖南岳阳人,硕士,主要研究方向为数据驱动控制和复杂网络。

收稿日期: 2023-10-11

  修回日期: 2023-11-06

  网络出版日期: 2025-06-03

基金资助

国家自然科学基金(62373206);青岛大学系统科学+联合研究项目(XT2024101)

Model Free Adaptive Pinning Control for Complex Network

  • TAO Zhao ,
  • HOU Zhongsheng ,
  • TAO Zhao ,
  • HOU Zhongsheng
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  • School of Automation, Qingdao University, Qingdao 266071, China

Received date: 2023-10-11

  Revised date: 2023-11-06

  Online published: 2025-06-03

摘要

针对复杂网络结构复杂、难以建模、控制器设计困难等问题,提出了对带有未知非线性耦合复杂网络的无模型自适应牵制控制方案。首先选取牵制控制节点,并基于受控节点上测量得到的输入输出数据对受控网络未知动力学模型作动态线性化数据建模,然后在最小方差准则下推导出相应控制器,从而设计出完全分布式的牵制控制方案。该方案设计仅需网络的输入输出数据而不依赖于复杂网络的模型,是一种数据驱动的牵制控制方法。同步稳定性结论则是基于简约定理、压缩映射和虚拟控制三种方法相结合得到的。仿真结果表明,该方案能够通过牵制控制网络中的少数节点,有效地驱动网络中的所有节点达到同步。

本文引用格式

陶昭 , 侯忠生 , 陶昭 , 侯忠生 . 复杂网络的无模型自适应牵制控制[J]. 复杂系统与复杂性科学, 2025 , 22(2) : 120 -127 . DOI: 10.13306/j.1672-3813.2025.02.015

Abstract

For the difficulties of modeling and designing proper controllers for complex network control problems, a model free adaptive control based pinning scheme is proposed to control complex network with unknown and nonlinear coupled relationship in this paper. Firstly, a dynamical linearization model is built based on input/output data of selected pinning node, then a distributed pinning scheme is proposed under minimum variance estimation criterion. This scheme is a data-driven control method because it is designed only with I/O data of pinned nodes instead of network model. The stability analysis for the synchronization error is based on the reduction theorem, contraction mapping method and virtual control. The simulation results demonstrate that the proposed pinning scheme can drive all nodes in network to synchronization states by only control the pinned nodes in network.

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