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Double Model Following Adaptive Control for a Complex Dynamical Network.

Xiaoxiao Li1, Yinhe Wang1, Shengping Li2

  • 1School of Automation, Guangdong University of Technology, Guangzhou 510006, China.

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|January 21, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel adaptive control method for complex dynamical networks (CDNs) by treating them as composite systems. The new approach enables simultaneous control of both network nodes and links, even when link states are unobservable.

Keywords:
complex dynamical networkdouble model following adaptive controllinks groupnodes group

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Area of Science:

  • Control Theory
  • Network Science
  • Dynamical Systems

Background:

  • Complex dynamical networks (CDNs) are prevalent in various fields, but controlling both their nodes and links simultaneously presents significant challenges.
  • Existing model-following adaptive control (MFAC) methods often struggle with unobservable link states due to practical constraints.

Purpose of the Study:

  • To formulate and solve a novel problem of double model-following adaptive control (MFAC) for both nodes and links in a complex dynamical network (CDN).
  • To develop an adaptive control scheme that overcomes the limitations of unobservable link states in CDNs.

Main Methods:

  • Viewing the CDN as a composite system comprising interconnected node and link groups (NG and LG).
  • Utilizing Lyapunov theory and novel mathematical preliminaries to design an adaptive control scheme for the NG.
  • Synthesizing the LG's coupling term with the NG's adaptive control to address the double MFAC problem.

Main Results:

  • A new adaptive control scheme is proposed for the node group (NG) of a CDN.
  • The proposed method successfully achieves double MFAC for both nodes and links, even when link states are unavailable.
  • Simulation results validate the effectiveness of the developed theoretical framework.

Conclusions:

  • The composite system perspective offers a new paradigm for CDN control.
  • The developed double MFAC strategy effectively manages complex network dynamics under state-unavailability constraints.
  • This research advances adaptive control techniques for interconnected systems.