Browsing USN Open Archive by Author "Esbensen, Kim H."
Now showing items 1-5 of 5
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A didactically motivated PLS prediction algorithm
Ergon, Rolf; Esbensen, Kim H. (Journal article; Peer reviewed, 2001)The intention of this paper is to develop an easily understood PLS prediction algorithm, especially for the control community. The algorithm is based on an explicit latent variables model, and is otherwise a combination ... -
Acoustic chemometric prediction of total solids in bioslurry: A full-scale feasibility study for on-line biogas process monitoring
Ihunegbo, Felicia Nkem; Madsen, Michael; Esbensen, Kim H.; Holm-Nielsen, Jens Bo; Halstensen, Maths (Journal article; Peer reviewed, 2012)Dry matter is an important process control parameter in the bioconversion application field. Acoustic chemometrics, as a Process Analytical Technology (PAT) modality for quantitative characterisation of dry matter in complex ... -
Acoustic chemometrics for material composition quantification in pneumatic conveying - The critical role of representative reference sampling
Wagner, Claas; Ihunegbo, Felicia Nkem; Halstensen, Maths; Esbensen, Kim H. (Journal article; Peer reviewed, 2012)Reliable monitoring of pneumatically conveyed particulate materials is critical for online detection and controlling material composition changes in the regimen of Process Analytical Technology (PAT), e.g. as the case ... -
Estimation, system identification and chemometrics
Ergon, Rolf; Di Ruscio, David Luigi; Esbensen, Kim H.; Hagen, Svein Thore (Conference report, 2000)In our master degree program in process automation, traditional modeling and control courses are supplemented by courses in experimental design and chemometrics. A corresponding inter-disciplinary research program supports ... -
PCR/PLSR optimization based on noise covariance estimation and Kalman filtering theory
Ergon, Rolf; Esbensen, Kim H. (Journal article; Peer reviewed, 2002)The theoretical connection between principal component regression (PCR) and partial least squares regression (PLSR) on one hand and Kalman filtering (KF) on the other is known from earlier work. In the present paper we ...