CIESC Journal

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基于混合建模技术的复合肥养分含量MIMO软测量模型

傅永峰; 苏宏业; 褚健   

  1. National Laboratory of Industrial Control Technology, Institute of Advanced Process
    Control, Zhejiang University, Hangzhou 310027, China
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-08-28 发布日期:2007-08-28
  • 通讯作者: 傅永峰

MIMO soft-sensor model of nutrient content for compound fertilizer based on hybrid modeling
technique

FU Yongfeng; SU Hongye; CHU Jian   

  1. National Laboratory of Industrial Control Technology, Institute of Advanced Process
    Control, Zhejiang University, Hangzhou 310027, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-08-28 Published:2007-08-28
  • Contact: FU Yongfeng

摘要: In compound fertilizer production, several quality variables need to be monitored and
controlled simul-taneously. It is very difficult to measure these variables on-line by
existing instruments and sensors. So, soft-sensor technique becomes an indispensable method
to implement real-time quality control. In this article, a new model of multi-inputs multi
-outputs (MIMO) soft-sensor, which is constructed based on hybrid modeling technique, is
pro-posed for these interactional variables. Data-driven modeling method and simplified
first principle modeling method are combined in this model. Data-driven modeling method
based on limited memory partial least squares (LM-PLS) algorithm is used to build soft-
senor models for some secondary variables; then, the simplified first prin-ciple model is
used to compute three primary variables on line. The proposed model has been used in
practical process; the results indicate that the proposed model is precise and efficient,
and it is possible to realize on line quality control for compound fertilizer process.

关键词: multi-inputs multi-outputs;soft-sensor;limited memory partial least squares;simplified first principle model;nutrient content of compound fertilizer

Abstract: In compound fertilizer production, several quality variables need to be monitored and
controlled simul-taneously. It is very difficult to measure these variables on-line by
existing instruments and sensors. So, soft-sensor technique becomes an indispensable method
to implement real-time quality control. In this article, a new model of multi-inputs multi
-outputs (MIMO) soft-sensor, which is constructed based on hybrid modeling technique, is
pro-posed for these interactional variables. Data-driven modeling method and simplified
first principle modeling method are combined in this model. Data-driven modeling method
based on limited memory partial least squares (LM-PLS) algorithm is used to build soft-
senor models for some secondary variables; then, the simplified first prin-ciple model is
used to compute three primary variables on line. The proposed model has been used in
practical process; the results indicate that the proposed model is precise and efficient,
and it is possible to realize on line quality control for compound fertilizer process.

Key words: multi-inputs multi-outputs, soft-sensor, limited memory partial least squares, simplified first principle model, nutrient content of compound fertilizer