Naslov
Adaptive Soft Sensor for Online Prediction Based on Moving Window Gaussian Process Regression

Autori
Grbić, Ratko ; Slišković, Dražen ; Kadlec, Petr

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Special Session VI: Adaptive and Dynamic Modeling in Non-stationary Environments / - , 2012, 428-433

ISBN
978-0-7695-4913-2

Skup
11th International Conference on Machine Learning and Applications (ICMLA 2012)

Mjesto i datum
Boca Raton (FL), Sjedinjene Američke Države, 12.12.2012. - 15.12.2012

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
process modeling; online prediction; Mutual Information; adaptive soft sensor; Gaussian Process Regression

Sažetak
Very often important process variables cannot be measured online due to low sampling rate of sensors or because their values have to be obtained by laboratory analysis. In order to enable continuous process monitoring and efficient process control in such cases, soft sensors are usually used to estimate these difficult-to- measure process variables. Most industrial processes exhibit some kind of time-varying behavior. To ensure that soft sensor retains its precision, adaptation mechanism has to be implemented. In this paper adaptive soft sensor based on Gaussian Process Regression (GPR) is presented. To make GPR model training more efficient, algorithm for variable selection based on Mutual Information is proposed. Prediction capabilities of the proposed method are examined on real industrial data obtained at an oil distillation column.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Temeljne tehničke znanosti

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