An experimental study of model predictive control based on artificial neural networks

被引：0
|
作者：
Chu, JZ
Tsai, PF
Tsai, WY
Jang, SS
Wong, DSH
Shieh, SS
Lin, PH
Jiang, SJ [1 ]
机构：
[1] Beijing Univ Chem Technol, Dept Automat, Beijing, Peoples R China
[2] Natl Tsing Hua Univ, Dept Chem Engn, Hsinchu, Taiwan
[3] Chang Jung Univ, Dept Occupat Safety & Hyg, Tainan, Taiwan
[4] Nanya Inst Technol, Dept Chem Engn, Taoyuan, Taiwan
[5] China Petr Corp, Chiayi, Taiwan
来源：
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS | 2003年 / 2773卷
关键词：
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：
Practical implementations of two typical types of artificial neural networks (ANNs), feedforward networks and external recurrent networks, as the model for model predictive control (MPC) were performed on the dual temperature control problem of two distillation columns, a pilot scale i-butane and n-butane distillation column and a bench scale ethanol and water column. The superiority of MPC based on an ANN models over conventional proportional-integral controllers and over dynamic matrix control were testified through experiments.
引用
收藏
页码：1296 / 1302
页数：7
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