A Data-Driven Approach to Control of Batch Processes With an Application to a Gravimetric Blender

被引：18

作者：

Formentin, Simone ^{[1
]}

Cologni, Alberto L. ^{[1
]}

Previdi, Fabio ^{[1
]}

Savaresi, Sergio M. ^{[2
]}

机构：

[1] Univ Bergamo, Lab Automat, Dipartimento Ingn, I-24044 Dalmine, Italy

[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy

来源：

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2014年 / 61卷 / 11期

关键词：

Batch processes; data-driven control; dosing; polymers; principal component analysis (PCA); ITERATIVE LEARNING CONTROL; NEURAL-NETWORKS; CONTROL-SYSTEMS; IDENTIFICATION; EXTRUSION; DESIGN;

D O I：

10.1109/TIE.2014.2308158

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a data-driven controller design approach for batch processes is proposed. In this strategy, based on a suitable transformation of the input and output signals, a mathematical description of the process dynamics is not needed, and the working cycle is guaranteed to adapt to the desired operating conditions. Throughout this paper, all the steps of the above algorithm are described in detail with the help of an experimental case study dedicated to a gravimetric blender, which is a key element in the plastic extrusion process.

引用

页码：6383 / 6390

页数：8

共 28 条

[1] Iterative Learning Control for Sampled-Data Systems: From Theory to Practice [J].