Performance-optimized applied identification of separable distributed-parameter processes

Citation
D. Gorinevsky et M. Heaven, Performance-optimized applied identification of separable distributed-parameter processes, IEEE AUTO C, 46(10), 2001, pp. 1584-1589
Citations number
14
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN journal
00189286 → ACNP
Volume
46
Issue
10
Year of publication
2001
Pages
1584 - 1589
Database
ISI
SICI code
0018-9286(200110)46:10<1584:PAIOSD>2.0.ZU;2-2
Abstract
This note studies practical algorithms for parametric identification of cro ss-directional processes from input/output data. Instead of working directl y with the original two-dimensional array of the high-resolution profile sc ans, the proposed algorithms use separation properties of the problem. It i s demonstrated that by estimating and identifying in turn cross-directional and time responses of the process, it is possible to obtain unbiased least -square error estimates of the model parameters. At each step, a single dat a sequence is used for identification which ensures high computational perf ormance of the proposed algorithm. A theoretical proof of algorithm converg ence is presented. The discussed algorithms are implemented in an industria l identification tool and this note includes a real-life example using pape r machine data.