Distributed optimal control for multi-agent trajectory optimization

This paper presents a novel optimal control problem, referred to as distributed optimal control, that is applicable to multiscale dynamical systems comprised of numerous interacting agents. The system performance is represented by an integral cost function of the macroscopic state that is optimized subject to a hyperbolic partial differential equation known as the advection equation. The microscopic control laws are derived from the optimal macroscopic description using a potential function approach. The optimality conditions of the distributed optimal control problem are first derived analytically and, then, demonstrated numerically through a multi-agent trajectory optimization problem. © 2013 The Authors. Published by Elsevier Ltd. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Foderaro, G; Ferrari, S; Wettergren, TA

Published Date

  • January 2014

Published In

Volume / Issue

  • 50 / 1

Start / End Page

  • 149 - 154

International Standard Serial Number (ISSN)

  • 0005-1098

Digital Object Identifier (DOI)

  • 10.1016/j.automatica.2013.09.014

Language

  • eng

Citation Source

  • Scopus