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المؤلفMjalli, F. S.
تاريخ الإتاحة2015-11-05T10:21:00Z
تاريخ النشر2006
اسم المنشورChemical Engineering & Technology
المصدرWiley Online library
الاقتباسMjalli, F. S. (2006), Adaptive and Predictive Control of Liquid-Liquid Extractors Using Neural-Based Instantaneous Linearization Technique. Chem. Eng. Technol., 29: 539–549.
الرقم المعياري الدولي للكتاب1521-4125
معرّف المصادر الموحدhttp://dx.doi.org/10.1002/ceat.200500271
معرّف المصادر الموحدhttp://hdl.handle.net/10576/3711
الملخصNonlinearity of the extraction process is addressed via the application of instantaneous linearization to control the extract and raffinate concentrations. Two feed-forward neural networks with delayed inputs and outputs were trained and validated to capture the dynamics of the extraction process. These nonlinear models were then adopted in an instantaneous linearization algorithm into two control algorithms. The self-tuning adaptive control strategy was compared to an approximate model predictive control in terms of set point tracking capability, efficiency and stability. For the case of large, abrupt set point changes, the performance of the self-tuning algorithm was poor, especially for the raffinate control. The approximate model predictive control strategy was superior to the self-tuning control in terms of its ability to force the output to following the set point trajectory efficiently with smooth controller moves.
اللغةen
الناشرWILEY-VCH Verlag GmbH & Co.
الموضوعExtraction
Modeling
Neural networks
Process control
العنوانAdaptive and Predictive Control of Liquid-Liquid Extractors Using Neural-Based Instantaneous Linearization Technique
النوعArticle
رقم العدد5
رقم المجلد29
dc.accessType Abstract Only


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