NDLI: Design of online soft sensors based on combined adaptive PCA and DMLP neural networks

Content Provider	IEEE Xplore Digital Library
Author	Salahshoor, K. Kordestani, M. Khoshro, M.S.
Copyright Year	2009
Description	Author affiliation: Department of Instrumentation and Automation, Petroleum University of Technology, Iran (Salahshoor, K.) \|\| Department of Control Engineering, Islamic Azad University South Tehran branch, Iran (Kordestani, M.; Khoshro, M.S.)
Abstract	An accurate on-line measurement of important quality variables is essential for successful monitoring and controlling of chemical process. However, these variables are usually difficult to measure on-line due to the limitations such as the time delay, high cost and reliability considerations. To overcome this problem, two online soft sensors are proposed based upon a combined adaptive principal component analysis (PCA) and a dynamic multi-layered perceptron (DMLP) artificial neural network (ANN). For this purpose, a recursive PCA and a PCA based on a sliding window are presented to adaptively extract the inherent features inside the measurements with high dimensions. The extracted low-dimension features are then used recursively as the main inputs to the DMLP networks. The developed online soft sensors are finally tested on a highly nonlinear distillation column benchmark problem to illustrate their comparative performances. The simulation results demonstrate the superiority of the soft sensor based on the recursive PCA and the DMLP network.
Starting Page	3481
Ending Page	3486
File Size	162398
Page Count	6
File Format	PDF
ISBN	9781424427222
DOI	10.1109/CCDC.2009.5192459
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Chemical sensors Delay effects Process control Artificial neural networks Time measurement Chemical processes Neural network PCA Neural networks soft sensor Feature extraction Industrial distillation column Monitoring Principal component analysis
Content Type	Text
Resource Type	Article

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