A ferrous iron concentration prediction model for the process of iron precipitation by goethite

作者：Xie, Shi-Wen; Xie, Yong-Fang; Yang, Chun-Hua; Jiang, Zhao-Hui^*; Gui, Wei-Hua

来源：Acta Automatica Sinica, 2014, 40(5): 830-837.

DOI：10.3724/SP.J.1004.2014.00830

• Continuous stirred tank reactor
• Double particle swarm optimization (DPSO)
• Information exchanges
• Integrated prediction models
• Iron precipitation
• Least squares support vector machines
• Mechanism model
• Variation tendencies

The reactor outlet ferrous iron concentration of iron precipitation process by goethite is obtained by off-line analysis with a long time delay, which leads to difficult real-time control for removing iron process. It is significant to research the reactor outlet ferrous iron concentration on-line prediction method for this problem. On the basis of analyzing the chemical reaction mechanism in the iron precipitation process, by integrating the influence of copper ions to the reaction process and the feature of continuous stirred tank reactor (CSTR), the mechanism model for the iron precipitation process is established in this paper. The double particle swarm optimization (DPSO) algorithm based on information exchange is proposed to determine the parameters in the mechanism model, and the error compensation model for the mechanism model is built with least squares support vector machine (LS-SVM). The ferrous iron concentration integrated predicting model is established by the mode of parallel connection with compensation. The application results demonstrate that the integrated prediction model can effectively reflect the variation tendency of ferrous iron concentration, which may give a foundation for the optimization control in the procedure of iron precipitation by goethite.

• 出版日期2014-5
• 单位中南大学