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المؤلفMjalli, Farouq
تاريخ الإتاحة2010-01-07T10:21:06Z
تاريخ النشر2004-07-30
اسم المنشورChemical Engineering Science
المعرّفhttp://dx.doi.org/10.1016/j.ces.2004.07.117
الاقتباسFarouq S. Mjalli, Neural network model-based predictive control of liquid–liquid extraction contactors, Chemical Engineering Science, Volume 60, Issue 1, January 2005, Pages 239-253
معرّف المصادر الموحدhttp://hdl.handle.net/10576/10637
الملخصThe 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.
اللغةen
الناشرElsevier Ltd
الموضوعNeural networks
Model predictive control
Modeling
Dynamic simulation
Liquid–liquid extraction
Scheibel column
العنوانNeural network model-based predictive control of liquid–liquid extraction contactors
النوعArticle
dc.accessType Abstract Only


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