Time-Dependent Networks: Prediction, Disruption, and Control Final Report: FY2019-FY2023

Abstract

We solve the problem of predicting and controlling nonlinear dynamical networks under random perturbations and targeted attacks, with applications to general communication networks. We expect our new theory and tools to impact the control of networked sensors and complex coupled systems with broad science benefits to national defense by identifying general mechanisms and pathways through which nonlinear dynamical networks collapse, and how distributed control and adaptive topology can be used to retain network functionality.

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Document Details

Document Type
Technical Report
Publication Date
Oct 06, 2023
Accession Number
AD1213891

Entities

People

  • Ira B. Schwartz

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Autonomous Systems
  • Availability
  • Classification
  • Communication Networks
  • Complex Systems
  • Computer Networks
  • Contracts
  • Covid-19
  • Department Of Defense
  • Disease Outbreaks
  • Dynamics
  • Electrical Grids
  • Infectious Diseases
  • Information Operations
  • Instability
  • Instructions
  • Intervention
  • Load Monitoring
  • Mean Field Theory
  • Mechanical Engineering
  • Mixed Reality
  • Monitoring
  • National Security
  • Nonlinear Dynamics
  • Nonlinear Systems
  • Physics
  • Robotics
  • Security
  • Switching

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Control Systems Engineering.
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