کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5000318 1460682 2017 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nonlinear model predictive control of a batch fluidized bed dryer for pharmaceutical particles
ترجمه فارسی عنوان
کنترل پیش بینی کننده غیرخطی مدل خشک کننده بستر سیلیکا برای ذرات دارویی
کلمات کلیدی
کنترل پیش بینی نشده غیر خطی، مدل پدیده شناسی برآورد افقی متحرک، خشک کن بستر سیال، طیف سنجی نزدیک به مادون قرمز،
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی هوافضا
چکیده انگلیسی
The availability of reliable online moisture content measurements exploiting near-infrared (NIR) spectroscopy and chemometric tools allows the application of online control strategies to a wide range of drying processes in the pharmaceutical industry. In this paper, drying of particles with a pilot-scale batch fluidized bed dryer (FBD) is studied using a in-line NIR probe. A consolidated phenomenological state-space model of an FBD based on mass and energy balances is calibrated applying a nonlinear least-square identification to experimental data (grey-box modeling). Then, relying on the calibrated model, a nonlinear model predictive controller and a moving horizon state estimator are designed. The objective is to reach a specific particle moisture content setpoint at the end of the drying batch while decreasing cycle time and limiting particle temperature. A penalty term on the energy consumption can also be added to the usual tracking control cost function. Compared to a typical FBD operation in industry (mostly open-loop), it is shown that the drying time and the energy consumption can be efficiently managed on the pilot-scale process while limiting various operation problems like under drying, over drying, or particles overheating.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Control Engineering Practice - Volume 64, July 2017, Pages 88-101
نویسندگان
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