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Adaptive fixed-time output synchronization for complex dynamical networks with multi-weights.

Yuting Cao1, Linhao Zhao2, Qishui Zhong1

  • 1School of Aeronautics and Astronautics, University of Electronic Science and Technology, Chengdu, 611731, China.

Neural Networks : the Official Journal of the International Neural Network Society
|April 6, 2023
PubMed
Summary
This summary is machine-generated.

This study achieves fixed-time output synchronization for complex dynamical networks with multi-weights using adaptive control. The methods ensure synchronization within a predictable, finite time, verified by simulations.

Keywords:
Adaptive controlComplex dynamical networksFixed-time output synchronizationMultiple weights

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Area of Science:

  • Control Theory
  • Network Science
  • Dynamical Systems

Background:

  • Complex dynamical networks with multi-weights (CDNMWs) present challenges in synchronization.
  • Achieving synchronization within a fixed time is crucial for many applications.

Purpose of the Study:

  • To investigate fixed-time output synchronization for two types of CDNMWs.
  • To develop and apply adaptive control methods for achieving this synchronization.
  • To establish theoretical criteria for fixed-time output synchronization.

Main Methods:

  • Formulation of complex dynamical networks with multi-weights and multiple couplings.
  • Development of fixed-time output synchronization criteria using Lyapunov functional and inequality techniques.
  • Application of two distinct adaptive control strategies.

Main Results:

  • Successfully addressed fixed-time output synchronization problems for the studied networks.
  • Derived theoretical criteria guaranteeing synchronization within a finite, predetermined time.
  • Demonstrated the efficacy of the proposed adaptive control methods through numerical simulations.

Conclusions:

  • The proposed adaptive control methods effectively achieve fixed-time output synchronization for CDNMWs.
  • The theoretical criteria provide a solid foundation for designing controllers for such networks.
  • Numerical simulations validate the analytical findings and the practical applicability of the methods.