Intelligent integrated optimization and control system for lead-zinc sintering process

Min Wu; Chen Hua Xu; Jin Hua She; Ryuichi Yokoyama

doi:10.1016/j.conengprac.2008.07.007

Intelligent integrated optimization and control system for lead-zinc sintering process

Min Wu, Chen Hua Xu, Jin Hua She^*, Ryuichi Yokoyama

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

29 Citations (Scopus)

Abstract

The lead-zinc sintering process (LZSP) is an important step in imperial smelting. This paper presents an intelligent integrated optimization and control system (IIOCS) for the LZSP. The optimization and control scheme has a hierarchical configuration. First, the requirements of process control and the configuration of the IIOCS are described. Then, models for predicting quantity and quality (Q&Q) are established using correlation and mechanism analysis, and are implemented by improved back-propagation neural networks. Based on the models, an integrated algorithm combining c-means clustering, genetic, and chaos approaches is employed to optimize the operating parameters of the process. Finally, the control of the process state is carried out by a distributed control system to control the Q&Q of the product.

Original language	English
Pages (from-to)	280-290
Number of pages	11
Journal	Control Engineering Practice
Volume	17
Issue number	2
DOIs	https://doi.org/10.1016/j.conengprac.2008.07.007
Publication status	Published - 2009 Feb

Keywords

Hierarchical configuration
Intelligent integrated control
Intelligent integrated optimization
Lead-zinc sintering process
Prediction model
Quantity and quality

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering
Applied Mathematics
Computer Science Applications

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10.1016/j.conengprac.2008.07.007

Cite this

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title = "Intelligent integrated optimization and control system for lead-zinc sintering process",

abstract = "The lead-zinc sintering process (LZSP) is an important step in imperial smelting. This paper presents an intelligent integrated optimization and control system (IIOCS) for the LZSP. The optimization and control scheme has a hierarchical configuration. First, the requirements of process control and the configuration of the IIOCS are described. Then, models for predicting quantity and quality (Q&Q) are established using correlation and mechanism analysis, and are implemented by improved back-propagation neural networks. Based on the models, an integrated algorithm combining c-means clustering, genetic, and chaos approaches is employed to optimize the operating parameters of the process. Finally, the control of the process state is carried out by a distributed control system to control the Q&Q of the product.",

keywords = "Hierarchical configuration, Intelligent integrated control, Intelligent integrated optimization, Lead-zinc sintering process, Prediction model, Quantity and quality",

author = "Min Wu and Xu, {Chen Hua} and She, {Jin Hua} and Ryuichi Yokoyama",

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doi = "10.1016/j.conengprac.2008.07.007",

language = "English",

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journal = "Control Engineering Practice",

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AU - Wu, Min

AU - Xu, Chen Hua

AU - She, Jin Hua

AU - Yokoyama, Ryuichi

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AB - The lead-zinc sintering process (LZSP) is an important step in imperial smelting. This paper presents an intelligent integrated optimization and control system (IIOCS) for the LZSP. The optimization and control scheme has a hierarchical configuration. First, the requirements of process control and the configuration of the IIOCS are described. Then, models for predicting quantity and quality (Q&Q) are established using correlation and mechanism analysis, and are implemented by improved back-propagation neural networks. Based on the models, an integrated algorithm combining c-means clustering, genetic, and chaos approaches is employed to optimize the operating parameters of the process. Finally, the control of the process state is carried out by a distributed control system to control the Q&Q of the product.

KW - Hierarchical configuration

KW - Intelligent integrated control

KW - Intelligent integrated optimization

KW - Lead-zinc sintering process

KW - Prediction model

KW - Quantity and quality

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Intelligent integrated optimization and control system for lead-zinc sintering process

Abstract

Keywords

ASJC Scopus subject areas

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