Multi-objective pole placement with evolutionary algorithms

Authors:
Gustavo Sánchez;Minaya Villasana;Miguel Strefezza
Affiliations:
Universidad Simón Bolívar, Venezuela;Universidad Simón Bolívar, Venezuela;Universidad Simón Bolívar, Venezuela
Venue:
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Year:
2007

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Abstract

Multi-Objective Evolutionary Algorithms (MOEA) have been succesfully applied to solve control problems. However, many improvements are still to be accomplished. In this paper a new approach is proposed: the Multi-Objective Pole Placement with Evolutionary Algorithms (MOPPEA). The design method is based upon using complex-valued chromosomes that contain information about closed-loop poles, which are then placed through an output feedback controller. Specific cross-over and mutation operators were implemented in simple but efficient ways. The performance is tested on a mixed multi-objective H2/H∞ control problem.