Fuzzy ant colony optimization for optimal control

Authors:
Jelmer Van Ast;Robert Babuška;Bart De Schutter
Affiliations:
Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands;Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands;Delft Center for Systems and Control, Delft University of Technology, Delft, The Netherlands and Marine and Transport Technology Department, Delft University of Technology
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

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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.