Journal of Guangdong University of Technology ›› 2022, Vol. 39 ›› Issue (05): 75-82.doi: 10.12052/gdutxb.220065

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Distributed Model-Free Adaptive Control for Nonlinear Multi-Agent Systems with FDI Attacks

Qu Shen1,2, Che Wei-wei1,2   

  1. 1. School of Automation, Qingdao University, Qingdao 266071, China;
    2. Shandong Key Laboratory of Industrial Control Technology, Qingdao University, Qingdao 266071, China
  • Received:2022-03-20 Published:2022-07-18

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Abstract: The distributed model-free adaptive control (DMFAC) problem for single-input single-output nonlinear multi-agent systems (MASs) with false data injection attacks is studied. A new distributed dynamic linearization method is proposed to obtain an equivalent distributed compact form dynamic linearization data model for nonlinear MASs. Unlike the existing DMFAC results of MASs that the network topology is used in the controller design, the distributed model-free adaptive controller designed in this research uses the input/output data and the controller parameter does not depend on the eigenvalues of the Laplacian matrix. Simulation examples verify that the proposed distributed model-free adaptive control algorithm can acheive bounded consensus control of MASs in the mean square sense. The algorithm can ensure that the multi-agent system achieve the consensus control objective when it is under attacks.

Key words: distributed compact form dynamic linearization, distributed model-free adaptive control, multi-agent systems, FDI (false data injection) attacks

CLC Number: 

  • TP273
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