Optimal Control through Biologically-Inspired Pursuit

Abstract

Inspired by the process by which ants gradually optimize their foraging trails, this paper investigates the cooperative solution of a class of free-final time, partially-constrained final state optimal control problems by a group of dynamic systems. A cooperative, pursuit-based algorithm is proposed for finding optimal solutions by iteratively optimizing an initial feasible control. The proposed algorithm requires only short-range, limited interactions between group members, and avoids the need for a "global map" of the environment on which the group evolves. The performance of the algorithm is illustrated in a series of numerical experiments.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2004
Accession Number
ADA439266

Entities

People

  • Cheng Shao
  • Dimitrios Hristu-varsakelis

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Autonomous Systems
  • Control Systems
  • Coordinate Systems
  • Dynamics
  • Electronic Mail
  • Maryland
  • Mechanical Engineering
  • Military Research
  • Optimization
  • Robotics
  • Robots
  • Self Organizing Systems
  • Sequences
  • Trajectories
  • Universities

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Calculus or Mathematical Analysis
  • Distributed Systems and Data Platform Development