Multi-objective pole placement with evolutionary algorithms

被引：0

作者：

Sanchez, Gustavo ^{[1
]}

Villasana, Minaya ^{[1
]}

Strefezza, Miguel ^{[1
]}

机构：

[1] Univ Simon Bolivar, Caracas 1080, Venezuela

来源：

EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PROCEEDINGS | 2007年 / 4403卷

关键词：

multi-objective control; pole placement; evolutionary algorithms;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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 H-2/H-infinity control problem.

引用

页码：417 / +

页数：3

共 13 条

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[2]

[Anonymous], 1995, THESIS U SHEFFIELD

[3]

Eiben A.E., 2015, Introduction to Evolutionary Computing

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