start-ver=1.4
cd-journal=joma
no-vol=2
cd-vols=
no-issue=
article-no=
start-page=837
end-page=842
dt-received=
dt-revised=
dt-accepted=
dt-pub-year=2004
dt-pub=20047
dt-online=
en-article=
kn-article=
en-subject=
kn-subject=
en-title=
kn-title=On-line actuator state monitoring of a MIMO bioprocess
en-subtitle=
kn-subtitle=
en-abstract=
kn-abstract=<p>In the actuator state monitoring of a time varying human multi-joint arm dynamics, typical issues are compounded by problems related to the uncertainty factor consisting of measurement noises and modeling error of the rigid body dynamics. In general, the uncertainty factor is under the case of non-Gaussian noises. In this paper, for improving the monitoring, a robust filter system based on a score function approach is modified. The score function is associated with U_D factorization algorithm. The selection of the shape parameter in the monitoring filter is discussed. Examples of the proposed method for an experiment-based human arm model show better accuracy and robustness compared with standard Kalman filter.</p>

en-copyright=
kn-copyright=

en-aut-name=DengMingcong
en-aut-sei=Deng
en-aut-mei=Mingcong
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=1
ORCID=

en-aut-name=InoueAkira
en-aut-sei=Inoue
en-aut-mei=Akira
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=2
ORCID=

en-aut-name=IshikawaKazushi
en-aut-sei=Ishikawa
en-aut-mei=Kazushi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=3
ORCID=

en-aut-name=HirashimaYoichi
en-aut-sei=Hirashima
en-aut-mei=Yoichi
kn-aut-name=
kn-aut-sei=
kn-aut-mei=
aut-affil-num=4
ORCID=

affil-num=1
en-affil=
kn-affil=Okayama University

affil-num=2
en-affil=
kn-affil=Okayama University 

affil-num=3
en-affil=
kn-affil=Okayama University

affil-num=4
en-affil=
kn-affil=Okayama University
en-keyword=MIMO systems
kn-keyword=MIMO systems
en-keyword=actuators
kn-keyword=actuators
en-keyword=condition monitoring
kn-keyword=condition monitoring
en-keyword=filtering theory
kn-keyword=filtering theory
en-keyword=physiological models
kn-keyword=physiological models
en-keyword=time-varying systems
kn-keyword=time-varying systems
END