Integrated Iterative Learning Control Strategy for Batch Processes

被引：0

作者：

Jia, Li ^{[1
]}

Yang, Tian ^{[1
]}

Chiu, Min-Sen ^{[2
]}

机构：

[1] Shanghai Univ, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China

[2] Natl Univ Singapore, Dept Chem & Biomol Engn, Singapore 117576, Singapore

来源：

COMPUTATIONAL INTELLIGENCE, NETWORKED SYSTEMS AND THEIR APPLICATIONS | 2014年 / 462卷

关键词：

batch process; integrated learning control; iterative learning control; Time-varying perturbation model; QUADRATIC OPTIMAL-CONTROL; DYNAMIC R-PARAMETER; MODEL; TRACKING;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An integrated iterative learning control strategy based on time-varying perturbation models for batch processes is proposed in this paper. A linear perturbation model is firstly obtained in order to control the perturbation variables rather than the actual process variables themselves. Next, an integrated control strategy which combines ILC with real-time feedback control is used to control the perturbation model. It leads to superior tracking performance and better robustness against disturbance and uncertainty. Lastly, the effectiveness of the proposed method is verified by examples.

引用

页码：419 / 427

页数：9

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