کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
172523 458547 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Iterative learning control for the systematic design of supersaturation controlled batch cooling crystallisation processes
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
Iterative learning control for the systematic design of supersaturation controlled batch cooling crystallisation processes
چکیده انگلیسی

The paper presents an approach to improve the product quality from batch-to-batch by exploiting the repetitive nature of batch processes to update the operating trajectories using process knowledge obtained from previous runs. The data based methodology is focused on using the linear time varying (LTV) perturbation model in an iterative learning control (ILC) framework to provide a convergent batch-to-batch improvement of the process performance indicator. The major contribution of this work is the development of a novel hierarchical ILC (HILC) scheme for systematic design of the supersaturation controller (SSC) of seeded batch cooling crystallizers. The HILC is used to determine the required supersaturation setpoint for the SSC and the corresponding temperature trajectory required to produce crystals with desired end-point property. The performance and robustness of these approaches are evaluated through simulation case studies. These results demonstrate the potential of the ILC approaches for controlling batch processes without rigorous process models.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Chemical Engineering - Volume 59, 5 December 2013, Pages 111–121
نویسندگان
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