TY - GEN
T1 - A design of a strongly stable generalized minimum variance control using a genetic algorithm
AU - Yanou, Akira
AU - Deng, Mingcong
AU - Inoue, Akira
PY - 2009/12/1
Y1 - 2009/12/1
N2 - This paper proposes a design scheme of generalized minimum variance control (GMVC) having a new design parameter. The design parameter is introduced by applying coprime factorization approach and Youla-Kucera parameterization of stabilizing compensators to a generalized minimum variance controller. And it is selected by using a genetic algorithm so that the controller is designed to be stable. Therefore the proposed method gives a strongly stable system, that is, not only the closed-loop system is stable, but also the controller itself is stable.
AB - This paper proposes a design scheme of generalized minimum variance control (GMVC) having a new design parameter. The design parameter is introduced by applying coprime factorization approach and Youla-Kucera parameterization of stabilizing compensators to a generalized minimum variance controller. And it is selected by using a genetic algorithm so that the controller is designed to be stable. Therefore the proposed method gives a strongly stable system, that is, not only the closed-loop system is stable, but also the controller itself is stable.
KW - Coprime factorization
KW - Generalized minimum variance control
KW - Genetic algorithm
KW - Strongly stable
UR - http://www.scopus.com/inward/record.url?scp=77951096930&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951096930&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77951096930
SN - 9784907764333
T3 - ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
SP - 1300
EP - 1304
BT - ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
T2 - ICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
Y2 - 18 August 2009 through 21 August 2009
ER -