TY - GEN
T1 - A design method of extended generalized minimum variance control based on state space approach by using a genetic algorithm
AU - Yanou, Akira
AU - Deng, Mingcong
AU - Inoue, Akira
PY - 2009/12/1
Y1 - 2009/12/1
N2 - This paper explores a selection method of the design parameter introduced in the extended Generalized Minimum Variance Control (GMVC) based on state-space approach by using a genetic algorithm. The extended controller has a new design parameter which can design the controller poles without changing the closed-loop poles, and the genetic algorithm is applied to find the new design parameter and select the controller poles.
AB - This paper explores a selection method of the design parameter introduced in the extended Generalized Minimum Variance Control (GMVC) based on state-space approach by using a genetic algorithm. The extended controller has a new design parameter which can design the controller poles without changing the closed-loop poles, and the genetic algorithm is applied to find the new design parameter and select the controller poles.
KW - Coprime factorization
KW - Generalized minimum variance control
KW - Genetic algorithm
KW - State space
UR - http://www.scopus.com/inward/record.url?scp=77951480477&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951480477&partnerID=8YFLogxK
U2 - 10.1109/ICICIC.2009.7
DO - 10.1109/ICICIC.2009.7
M3 - Conference contribution
AN - SCOPUS:77951480477
SN - 9780769538730
T3 - 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
SP - 189
EP - 192
BT - 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
T2 - 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009
Y2 - 7 December 2009 through 9 December 2009
ER -