Fuzzy Ant Colony Optimization for Optimal Control
Reference
J. van Ast,
R. Babuška, and
B. De Schutter,
"Fuzzy Ant Colony Optimization for Optimal Control," Proceedings of the 2009 American Control Conference,
St. Louis, Missouri, pp. 1003-1008, June 2009.
Abstract
Ant Colony Optimization (ACO) has proven to be a very powerful
optimization heuristic for Combinatorial Optimization Problems. While
being very successful for various NP-complete optimization problems,
ACO is not trivially applicable to control problems. In this paper a
novel ACO algorithm is introduced for the automated design of optimal
control policies for continuous-state dynamic systems. The so called
Fuzzy ACO algorithm integrates the multi-agent optimization heuristic
of ACO with a fuzzy partitioning of the state space of the system. A
simulated control problem is presented to demonstrate the functioning
of the proposed algorithm.
Downloads
- Corresponding technical report:
pdf
file
(1.20 MB)
Bibtex entry
@inproceedings{vanBab:09-001,
author={J. van Ast and R. Babu{\v{s}}ka and B. {D}e Schutter},
title={Fuzzy Ant Colony Optimization for Optimal Control},
booktitle={Proceedings of the 2009 American Control Conference},
address={St.\ Louis, Missouri},
pages={1003--1008},
month=jun,
year={2009}
}
This page is maintained by Bart De Schutter.
Last update: February 21, 2026.