Hybrid Modeling and Control of Nonlinear Wet Flue Gas Desulphurization Process

• Published in: 2007 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
• Language: English
• 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
• ISBN: 1424409721; 9781424409723
• ISSN: 2160-133X
• DOI: 10.1109/ICMLC.2007.4370239

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.