Managing Emergent Behavior in Distributed Control Systems

Abstract

Distributed control architectures are becoming increasingly popular because their modularity makes them easy to install, configure, and modify. These benefits do not come for free. A population of asynchronously executing processes without central top-down control can exhibit unexpected or emergent" behavior at the system level. To the plant engineer, this behavior may look lIke noise or error conditions, but it is generated by deterministic interactions among control elements, not random events or unit malfunctions, and it must be managed accordingly. Drawing on experiences in the Auto Body Consortium's Intelligent Resistance Welding project, we illustrate the potential for this kind of behavior among welding robots in an automotive body shop and in other applications, show how recent research in nonlinear systems theory and agent-based control can be used to detect and manage such interactions, and identify some requirements that these agent techniques place on emerging standards for data and control models.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1997
Accession Number
ADA361539

Entities

People

  • H. Van Dyke Parunak
  • Raymond S. Vanderbok

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Agent-Based Simulations
  • Automated Guided Vehicles
  • Control Systems
  • Engineers
  • Frequency
  • Linear Systems
  • Manufacturing
  • Materials
  • Mathematical Analysis
  • Nonlinear Systems
  • Operating Systems
  • Power Spectra
  • Quality Control
  • Research Facilities
  • Simulations
  • Supply Chain
  • Vehicles

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Control Systems Engineering.
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Autonomous System Control