Fuzzy ant colony optimization for optimal control

Reference:
J. van Ast, R. Babuska, 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.

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Corresponding technical report: pdf file (1.05 MB)
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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}
        }

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