Predictive Dynamic Modeling of Key Process Variables in Granulation Processes Using Partial Least Squares Approach-Reference-Cited by-同舟云学术

Predictive Dynamic Modeling of Key Process Variables in Granulation Processes Using Partial Least Squares Approach

Published:2011-01-04 Issue:3 Volume:50 Page:1419-1426
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Ronen Doron¹,Sanders Constantijn F. W.¹,Tan Hong Sing¹,Mort Paul R.¹,Doyle Francis J.¹

Affiliation:

1. Department of Chemical Engineering, University of California at Santa Barbara, Santa Barbara, California 93106-5080, United States, Procter & Gamble Technical Centre, Ltd. Whitley Road, Longbenton, Newcastle Upon Tyne, NE12 9TS U.K, and Procter & Gamble Co. 5299 Spring Grove Avenue, Cincinnati, Ohio 45217, United States

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ie100836w

Reference17 articles.

1. A multi-form modelling approach to the dynamics and control of drum granulation processes

2. Nucleation, growth and breakage phenomena in agitated wet granulation processes: a review

3. Ronen, D.; Sanders, C. F. W.; Tan, H. S.; Mort, P. R.; Doyle, F. J.Predictive Modeling of Key Process Variables in Granulation Processes Based on Dynamic Partial Least Squares, Proceedings of the ADCHEM Conference, IFAC, Istanbul, Turkey, 2009

4. Model predictive control: Theory and practice—A survey

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