dc.contributor.author | Ergon, Rolf | |
dc.date.accessioned | 2007-04-25T09:10:21Z | |
dc.date.accessioned | 2017-04-19T12:49:43Z | |
dc.date.available | 2007-04-25T09:10:21Z | |
dc.date.available | 2017-04-19T12:49:43Z | |
dc.date.issued | 1999 | |
dc.identifier.citation | IEEE transactions on automatic control 44(1999), No. 4, p. 821-825 | |
dc.identifier.issn | 0018-9286 | |
dc.identifier.uri | http://hdl.handle.net/11250/2438393 | |
dc.description | ©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | |
dc.description | ©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | |
dc.description.abstract | In many cases, vital output variables in, e.g., industrial processes cannot be measured online. It is then of interest to estimate these primary variables from manipulated and measured inputs and the secondary output measurements that are available. In order to identify an optimal estimator from input-output data, a suitable model structure must be chosen. The paper compares use of ARMAX and output error (OE) structures in prediction error identification methods, theoretically and through simulations. | |
dc.format.extent | 940242 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers | |
dc.subject | Estimation | |
dc.subject | Product quality | |
dc.subject | System identification | |
dc.title | On primary output estimation by use of secondary measurements as inputsignals in system identification | |
dc.type | Journal article | |
dc.type | Peer reviewed | |
dc.subject.nsi | 563 | |
dc.identifier.doi | http://dx.doi.org/10.1109/9.754826 | |