Parallel eigenstructure assignment via LQR design and genetic algorithms

Author

Bottura, Celso P. ; Neto, J. V da Fonseca

Author_Institution

UNICAMP, Campinas, Brazil

Volume

4

fYear

1999

fDate

1999

Firstpage

2295

Abstract

Eigenstructure assignment difficulties through linear quadratic regulator (LQR) control designs are associated to the weighting matrices Q and R determination for the algebraic Riccati equation (ARE), whose solutions give the controller K gains, that are able to assign specified eigenvalues and eigenvectors. This work proposes a methodology to solve these difficulties, and based on it and on parallel hybrid genetic algorithms and parallel solutions of the LQR problems, an efficient approach is also developed. Finally, the controller performance is verified on an aircraft model

Keywords

Riccati equations; aircraft control; asymptotic stability; eigenstructure assignment; genetic algorithms; linear quadratic control; matrix algebra; parallel algorithms; state feedback; LQR design; aircraft model; algebraic Riccati equation; genetic algorithms; linear quadratic regulator; parallel eigenstructure assignment; parallel hybrid genetic algorithms; weighting matrices; Algorithm design and analysis; Control design; Control systems; Cost function; Eigenvalues and eigenfunctions; Equations; Genetic algorithms; Performance gain; Regulators; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference, 1999. Proceedings of the 1999

Conference_Location

San Diego, CA

ISSN

0743-1619

Print_ISBN

0-7803-4990-3

Type

conf

DOI

10.1109/ACC.1999.786425

Filename

786425