MRCD: a genetic algorithm for multiobjective robust control design

A genetic algorithm (GA) for the class of multiobjective optimization problems that appears in the design of robust controllers is presented in this paper. The design of a robust controller is a trade-off problem among competitive objectives such as disturbance rejection, reference tracking, stabili...

Full description

Saved in:
Bibliographic Details
Published in:Engineering applications of artificial intelligence 2002-06, Vol.15 (3), p.285-301
Main Authors: Herreros, Alberto, Baeyens, Enrique, Perán, José R.
Format: Article
Language:English
Subjects:
Linear matrix inequalities
Mixed [formula omitted] control
Multiobjective genetic algorithms
Multiobjective optimization
Robust control design
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A genetic algorithm (GA) for the class of multiobjective optimization problems that appears in the design of robust controllers is presented in this paper. The design of a robust controller is a trade-off problem among competitive objectives such as disturbance rejection, reference tracking, stability against unmodeled dynamics, moderate control effort and so on. However, general methodologies for solving this class of design problems are not easily encountered in the literature because of the complexity of the resultant multiobjective problems. In this paper, a recently developed class of GAs, multiobjective GAs, are used to solve robust control design problems. Here, a new algorithm, called multiobjective robust control design, has been proposed. The structure and operators of this algorithm have been specifically developed for control design problems. The performace of the algorithm is evaluated by solving several test cases and is also compared to the standard algorithms used for the multiobjective design of robust controllers.
ISSN:0952-1976
1873-6769
DOI:10.1016/S0952-1976(02)00036-2