A Chaos-Based Iterated Multistep Predictor for Blast Furnace Ironmaking Process
A Chaos-Based Iterated Multistep Predictor for Blast Furnace Ironmaking Process
复制标题
基于混沌的高炉炼铁过程迭代多步预测器
DOI：
10.1002/aic.11724
复制
发表时间：
2009-04-01
期刊：
影响因子：
3.7
通讯作者：
Sun, Youxian
中科院分区：
文献类型：
--
作者：
Gao, Chuanhou;Chen, Jiming;Sun, Youxian
高炉炼铁过程中发生复杂的化学反应和迁移现象，给高炉内部热状态的预测和控制带来了很大的挑战。本文设计了一种基于混沌的迭代多步预报器，用于预测小型高炉铁水中的硅含量。预测值与观测值的合理吻合表明，所建立的高维混沌预报器能够很好地预测硅系的演化，从而有力地说明了复杂高炉炼铁过程动力学存在的确定性机制，即高维混沌系统适合用来描述高炉系统。这一结果可能为描述高炉炼铁过程的特性提供指导，这是一个极其复杂但令人着迷的领域，在未来的研究中具有混沌特性。(C)2009年美国化学工程师学会学报，55：947962,2009年
The prediction and control of the inner thermal state of a blast furnace, represented as silicon content in blast furnace hot metal, pose a great challenge because of complex chemical reactions and transfer phenomena taking place in blast furnace ironmaking process. In this article, a chaos-based iterated multistep predictor is designed for predicting the silicon content in blast furnace hot metal collected from a pint-sized blast furnace. The reasonable agreement between the predicted values and the observed values indicates that the established high dimensional chaotic predictor can predict the evolvement of silicon series well, which conversely render the strong indication of existing deterministic mechanism ruling the dynamics of complex blast furnace ironmaking process, i.e., a high-dimensional chaotic system is suitable for representing the blast furnace system. The results may serve as guidelines for characterizing blast furnace ironmaking process, an extremely complex but fascinating field, with chaos in the future investigation. (C) 2009 American Institute of Chemical Engineers AIChE J, 55: 947962, 2009