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Author Mjalli, Farouqen_US
Available date 2010-01-07T10:21:06Zen_US
Publication Date 2004-07-30en_US
Publication Name Chemical Engineering Science
Citation Farouq S. Mjalli, Neural network model-based predictive control of liquid–liquid extraction contactors, Chemical Engineering Science, Volume 60, Issue 1, January 2005, Pages 239-253en_US
URI http://dx.doi.org/10.1016/j.ces.2004.07.117en_US
URI http://hdl.handle.net/10576/10637en_US
Abstract The inherent complex nonlinear dynamic characteristics and time varying transients of the liquid–liquid extraction process draw the attention to the application of nonlinear control techniques. In this work, neural network-based control algorithms were applied to control the product compositions of a Scheibel agitated extractor of type I. Model predictive control algorithm was implemented to control the extractor. The extractor hydrodynamics and mass transfer behavior were modeled using the non-equilibrium backflow mixing cell model. It was found that model predictive control is capable of solving the servo control problem efficiently with minimum controller moves. This study will be followed by more work concentrated on using different neural network-based control algorithms for the control of extraction contactors.en_US
Language enen_US
Publisher Elsevier Ltden_US
Subject Neural networksen_US
Subject Model predictive controlen_US
Subject Modelingen_US
Subject Dynamic simulationen_US
Subject Liquid–liquid extractionen_US
Subject Scheibel columnen_US
Title Neural network model-based predictive control of liquid–liquid extraction contactorsen_US
Type Articleen_US


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