An Integrated Dynamic and Quality Modeling Framework for Batch Processes

被引:1
|
作者
Mhaskar, Aswin Prashant [1 ]
Mhaskar, Prashant [1 ]
机构
[1] McMaster Univ, Dept Chem Engn, Hamilton, ON L8S 4L8, Canada
来源
基金
加拿大自然科学与工程研究理事会;
关键词
Quality modelling; Batch processes; Prediction error minimization; SUBSPACE IDENTIFICATION APPROACH; ITERATIVE LEARNING CONTROL; TRAJECTORY TRACKING; PRODUCT QUALITY; PREDICTIVE CONTROL; OPTIMIZATION; MPC;
D O I
10.1016/j.cherd.2024.09.026
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This manuscript considers batch process operations and addresses the challenge of identifying a model that synergistically captures the dynamic input-output behavior of continuously measured variables along with the quality variables measured only at batch termination. To this end, an optimization-based framework is developed to identify one model that captures both the dynamics between the inputs and the continuously measured output variables, measurements of which are available at every time step, and the relation between the dynamic "state"information and the terminal quality measurements. Existing approaches either do not identify the dynamic and the quality model simultaneously, or they simply connect the whole trajectory of the process variables with the qualities and do not address the dynamic relationship between the inputs and the process variables. The improved modelling performance of the model obtained from this approach is demonstrated using data from a Uni-axial Rotational Molding process, and compared with existing modelling approaches.
引用
收藏
页码:698 / 706
页数:9
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