Structure and Input-Output Properties in Networks of Nonlinear Systems

Abstract

In this project we developed an input-output approach to predict and engineer collective behavior in networks. This approach overcomes the complexity of the large-scale, nonlinear dynamical model by dividing the analysis and design tasks into two layers: At the network layer, we represent the nodes with appropriate input-output properties as abstractions of their detailed models and exploit these properties in conjunction with the interconnection structure to ascertain desirable behaviors. At the network layer, we represent the nodes with appropriate input-output properties as abstractions of their detailed models and exploit these properties in conjunction with the interconnection structure to ascertain desirable behaviors. At the node layer, we study the individual dynamical models to verify or assign the input-output properties without relying on knowledge of global network properties.

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Document Details

Document Type
Technical Report
Publication Date
Aug 20, 2014
Accession Number
ADA609701

Entities

People

  • Murat Arcak

Organizations

  • University of California Regents

Tags

Communities of Interest

  • Cyber
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Air Force
  • Air Force Research Laboratories
  • Automatic
  • Biology
  • California
  • Cell Physiological Processes
  • Computer Science
  • Control Systems Engineering
  • Cooperative Control
  • Diffusion
  • Engineering
  • Engineers
  • Multiagent Systems
  • Nonlinear Systems
  • Oscillators
  • Synthetic Biology

Fields of Study

  • Computer science

Readers

  • Computational Fluid Dynamics (CFD)
  • Computer Networking
  • Distributed Systems and Data Platform Development