TY - GEN
T1 - An improvement of quasi-ARX predictor to control of nonlinear systems using nonlinear PCA network
AU - Wang, Lan
AU - Hu, Jinglu
PY - 2009
Y1 - 2009
N2 - In this paper, a nonlinear principal component analysis (NPCA) is introduced to improve the quasi-ARX modeling. One part of the quasi-ARX model is an ordinary neurofuzzy network to parameterize the coefficients which faces to a problem of high dimension. NPCA is used for this part to deal with the problem. The processes of modeling, parameter estimating and control are given detailedly. Some simulations of systems controlling are provided to illustrate the effectiveness of the proposed modeling approach.
AB - In this paper, a nonlinear principal component analysis (NPCA) is introduced to improve the quasi-ARX modeling. One part of the quasi-ARX model is an ordinary neurofuzzy network to parameterize the coefficients which faces to a problem of high dimension. NPCA is used for this part to deal with the problem. The processes of modeling, parameter estimating and control are given detailedly. Some simulations of systems controlling are provided to illustrate the effectiveness of the proposed modeling approach.
KW - Neurofuzzy network
KW - Nonlinear principal component analysis (NPCA)
KW - Nonlinear system
KW - Quasi-ARX model
UR - http://www.scopus.com/inward/record.url?scp=77951138885&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951138885&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:77951138885
SN - 9784907764333
T3 - ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
SP - 5095
EP - 5100
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 -