TY - JOUR
T1 - Recursive Identification Methods for Multivariate Output-error Moving Average Systems Using the Auxiliary Model
AU - Liu, Qinyao
AU - Ding, Feng
AU - Alsaedi, Ahmed
AU - Hayat, Tasawar
N1 - Publisher Copyright:
© 2018, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2018/6/1
Y1 - 2018/6/1
N2 - This paper studies the parameter identification problems of multivariate output-error moving average systems. An auxiliary model based extended stochastic gradient algorithm and based recursive extended least squares algorithm are proposed for estimating the parameters of the multivariate output-error moving average systems. By using the multi-innovation identification theory, an auxiliary model based multi-innovation extended stochastic gradient algorithm is derived for improving the parameter estimation accuracy. Finally, the simulation results indicate that the proposed algorithms can work well.
AB - This paper studies the parameter identification problems of multivariate output-error moving average systems. An auxiliary model based extended stochastic gradient algorithm and based recursive extended least squares algorithm are proposed for estimating the parameters of the multivariate output-error moving average systems. By using the multi-innovation identification theory, an auxiliary model based multi-innovation extended stochastic gradient algorithm is derived for improving the parameter estimation accuracy. Finally, the simulation results indicate that the proposed algorithms can work well.
KW - Auxiliary model
KW - multivariate system
KW - parameter estimation
KW - recursive identification
UR - http://www.scopus.com/inward/record.url?scp=85044731301&partnerID=8YFLogxK
U2 - 10.1007/s12555-017-0101-7
DO - 10.1007/s12555-017-0101-7
M3 - Article
AN - SCOPUS:85044731301
SN - 1598-6446
VL - 16
SP - 1070
EP - 1079
JO - International Journal of Control, Automation and Systems
JF - International Journal of Control, Automation and Systems
IS - 3
ER -