crta
Hrvatska znanstvena Sekcija img
bibliografija
3 gif
 Naslovna
 O projektu
 FAQ
 Kontakt
4 gif
Pregledavanje radova
Jednostavno pretraživanje
Napredno pretraživanje
Skupni podaci
Upis novih radova
Upute
Ispravci prijavljenih radova
Ostale bibliografije
Slični projekti
 Bibliografske baze podataka

Pregled bibliografske jedinice broj: 625909

Časopis

Autori: Slišković, Dražen; Grbić, Ratko; Hocenski, Željko
Naslov: Adaptive Estimation of Difficult-to-Measure Process Variables
Izvornik: Automatika : časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije (0005-1144) 54 (2013), 2; 166-177
Vrsta rada: članak
Ključne riječi: Process variable estimation; Adaptive estimator; Moving window; Recursive algorithms; JITL algorithm
Sažetak:
There exist many problems regarding process control in the process industry since some of the important variables cannot be measured online. This problem can be significantly solved by estimating these difficult-to-measure process variables. In doing so, the estimator is in fact an appropriate mathematical model of the process which, based on information about easy-to-measure process variables, estimates the current value of the difficult-to-measure variable. Since processes are usually time-varying, the precision of the estimation based on the process model which is built on old data is decreasing over time. To avoid estimator accuracy degradation, model parameters should be continuously updated in order to track process behavior. There are a couple of methods available for updating model parameters depending on the type of process model. In this paper, PLSR process model is chosen as the basis of the difficult-to-measure process variable estimator while its parameters are updated in several ways – by the moving window method, recursive NIPALS algorithm, recursive kernel algorithm and Just-in-Time learning algorithm. Properties of these adaptive methods are explored on a simulated example. Additionally, the methods are analyzed in terms of computational load and memory requirements.
Projekt / tema: 165-0361621-2000
Izvorni jezik: ENG
Rad je indeksiran u
bazama podataka:
Scopus
SCI-EXP, SSCI i/ili A&HCI
Science Citation Index Expanded (SCI-EXP) (sastavni dio Web of Science Core Collectiona)
Kategorija: Znanstveni
Znanstvena područja:
Računarstvo,Temeljne tehničke znanosti
Broj citata:
Altmetric:
DOI: 10.7305/automatika.54-2.147
URL cjelovitog teksta:
Časopis izlazi u samo elektroničkom izdanju: NE
Google Scholar: Adaptive Estimation of Difficult-to-Measure Process Variables
Upisao u CROSBI: Ratko Grbić (Ratko.Golubic@etfos.hr), 17. Tra. 2013. u 12:11 sati



Verzija za printanje   za tiskati


upomoc
foot_4