Robust soft sensor development using multi-rate measurements*. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Wu, Ouyang; Kodamana, Hariprasad; Jan, Nabil Magbool; Tan, Ruomu; Huang, Biao
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 10190
• Page End: 10195
• Publication Date: 2017-07
• Subjects: soft sensor -- static model -- multi-rate -- Expectation Maximization algorithm -- t—distribution -- flat-topped t—distribution; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.1768
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Two different types of measurements are often available for the key quality variables in process industries - (a) an accurate "slow-rate" laboratory measurements, and (b) a less accurate "fast-rate" online analyser measurements. Also, the analyser measurements are prone to fail due to hardware issues. Therefore, the main objective of this work is to present a novel approach for developing an accurate, fast-rate, inferential model of quality variables which is robust to outliers. For this purpose, we present a maximum likelihood based approach to integrate the multi-rate output data in the model building task, using Expectation Maximization algorithm. The efficacy of the proposed approach is demonstrated using a simulation example.