Biologically Inspired Algorithms for Optimal Control

Abstract

Cooperative control systems are increasingly emerging as significant alternatives to their centralized counterparts. The rising interest in deploying cooperative systems is fueled by the development of decentralized systems with low cost and performance advantages. For example, mobile exploration and information gathering tasks can often be accomplished cheaply and more reliably by swarms of small autonomous robots as opposed to a single more sophisticated one. Cooperative control is also applied in many tasks that can not be performed by a single system, e.g. satellite arrays that enable global communication, geographically remote systems that communicate via network and others. The goal of our research is to investigate optimal control in cooperative systems, using algorithms inspired from biology. We begin with a review of collective behavior in biological systems.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA439518

Entities

People

  • Cheng Shao
  • Dimitrios Hristu-varsakelis

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Autonomous Systems
  • Computations
  • Control Systems
  • Cooperative Control
  • Coordinate Systems
  • Dynamic Programming
  • Engineering
  • Environment
  • Equations
  • Mathematical Models
  • Probability
  • Simulations
  • Systems Biology
  • Time Intervals
  • Trajectories

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Economics
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control
  • Space
  • Space - Spacecraft Maneuvers