Ant colony optimization for optimal control

Reference:
J. van Ast, R. Babuska, and B. De Schutter, "Ant colony optimization for optimal control," Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC 2008), Hong Kong, pp. 2040-2046, June 2008.

Abstract:
Ant Colony Optimization (ACO) has proven to be a very powerful optimization heuristic for Combinatorial Optimization Problems (COPs). It has been demonstrated to work well when applied to various NP-complete problems, such as the traveling salesman problem. In this paper, an ACO approach to optimal control is proposed. This approach requires that a continuous-time, continuous-state model of the system, together with a finite action set, is formulated as a discrete, non-deterministic automaton. The control problem is then translated into a stochastic COP. This method is applied to the time-optimal swing-up and stabilization of a pendulum.

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Corresponding technical report: pdf file (176 KB)
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Bibtex entry:

@inproceedings{vanBaB:08-003,
        author={J. van Ast and R. Babu{\v{s}}ka and B. {D}e Schutter},
        title={Ant colony optimization for optimal control},
        booktitle={Proceedings of the 2008 IEEE Congress on Evolutionary Computation (CEC 2008)},
        address={Hong Kong},
        pages={2040--2046},
        month=jun,
        year={2008}
        }

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