Fuzzy ant colony optimization for optimal control

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.

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.

Corresponding technical report: pdf file (1.20 MB)

@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}
}

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