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Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
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Network synchronization of time-delayed coupled nonlinear systems using predictor-based diffusive dynamic couplings.

C Murguia1, Rob H B Fey1, H Nijmeijer1

  • 1Department of Mechanical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.

Chaos (Woodbury, N.Y.)
|March 2, 2015
PubMed
Summary
This summary is machine-generated.

This study addresses controlled network synchronization for coupled semipassive systems with time-delay. Predictor-based controllers ensure global state synchronization, enhancing network performance.

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Area of Science:

  • Control Systems Engineering
  • Networked Systems
  • Nonlinear Dynamics

Background:

  • Networked systems often involve time-delays in control signals and outputs.
  • Achieving synchronization in coupled systems with delays is a significant challenge.

Purpose of the Study:

  • To develop and analyze predictor-based controllers for controlled network synchronization of coupled semipassive systems with constant time-delays.
  • To establish conditions guaranteeing global state synchronization in such systems.

Main Methods:

  • Utilizing Lyapunov-Krasovskii functionals and the concept of semipassivity.
  • Designing predictor-based dynamic output feedback controllers.
  • Deriving sufficient conditions for synchronization based on system properties, network topology, coupling, and time-delays.

Main Results:

  • Proved global ultimate boundedness of interconnected system solutions under mild assumptions.
  • Derived sufficient conditions for global state synchronization.
  • Demonstrated that predictor-based control can increase the allowable time-delay in the network compared to static couplings.

Conclusions:

  • Predictor-based controllers are effective for achieving controlled network synchronization in semipassive systems with time-delays.
  • The proposed method enhances network robustness to time-delays.
  • Simulations with Hindmarsh-Rose neurons validate the theoretical findings.