Hybrid Modeling and Control of Nonlinear Wet Flue Gas Desulphurization Process

The optimization and control problem of Wet Flue Gas Desulphurization (WFGD) in power plant was studied. Mixed logical dynamical (MLD) model was built to describe hybrid phenomenon of the WFGD process. Based on the mixed logic dynamical model of WFGD, the predictive control optimization problem was...

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Bibliographic Details
Published in2007 International Conference on Machine Learning and Cybernetics Vol. 2; pp. 726 - 730
Main Authors Yun-Tao Shi, De-Hui Sun, Zhi-Jun Li, Nian-Si Chen, Wang Qing, Dongjie Gao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2007
Subjects
Cybernetics
Flue gases
Hybrid systems
Logic
Machine learning
Mixed integer quadratic program
Mixed logical dynamics
Optimal control
Poles and towers
Power generation
Power system modeling
Predictive control
Predictive models
Wet flue gas desulphurization
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ISBN1424409721
9781424409723
ISSN2160-133X
DOI10.1109/ICMLC.2007.4370239

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Summary:The optimization and control problem of Wet Flue Gas Desulphurization (WFGD) in power plant was studied. Mixed logical dynamical (MLD) model was built to describe hybrid phenomenon of the WFGD process. Based on the mixed logic dynamical model of WFGD, the predictive control optimization problem was solved using the Mixed Integer Quadratic program (MIQP) solver. Therefore the optimal discrete decision variable (the number of LG pump) and the continuous variable decision variable (PH set-point) were obtained on line. The real-time optimization was implemented. A MLD model of PH was also developed based on which the predictive controller of PH was designed. The simulation results indicate that the predictive control based on MLD model scheme presented had good effect.
ISBN:1424409721
9781424409723
ISSN:2160-133X
DOI:10.1109/ICMLC.2007.4370239