Ant colony optimization for optimal control

J. van Ast, R. Babuška, 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.

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.

Corresponding technical report: pdf file (333 KB)

@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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