自动化学报2016，Vol.42Issue(11)：1664-1679,16.DOI:10.16383/j.aas.2016.c150819
高炉炼铁过程多元铁水质量非线性子空间建模及应用
Nonlinear Subspace Modeling of Multivariate Molten Iron Quality in Blast Furnace Ironmaking and Its Application
摘要
Abstract
Blast furnace ironmaking is a nonlinear dynamic process containing complex physical-chemical reaction, multi-phase multi-field coupling and large time delay. Measuring, modeling and control of the key process indices of ironmaking process, molten iron quality (MIQ) parameters, have always been treated as a difficult problem in metallurgic engineer-ing and automation field. This paper presents a control oriented data-driven nonlinear subspace modeling method for multivariate prediction of MIQ. First, to improve modeling efficiency, data driven canonical correlation analysis (CCA) and correlation analysis (CA) are combined to pick out the most influential controllable variables from multitudinous factors to serve as the input variables of modeling. Second, to better reflect the nonlinear dynamic characteristics of blast furnace ironmaking process, the time series and time delays of the relevant input and output variables are taken into account. Finally, a data-driven nonlinear state-space model of MIQ is built using least square support vector machine (LS-SVM) based nonlinear subspace identification method for Hammerstein system. With polynomial fitting method, the nonlinear parts expressed by kernel functions in the obtained Hammerstein model are simplified, so as to greatly reduce the computational complexity of the model on the premise of only a small loss of accuracy. Industrial experiments based on real data verifies the accuracy, effectiveness and advancement of the proposed method.关键词
高炉炼铁/子空间辨识/Hammerstein模型/典型相关性分析/非线性系统建模/最小二乘支持向量机/多元铁水质量Key words
Blast furnace ironmaking/subspace identification/Hammerstein model/canonical correlation analysis (CCA)/nonlinear system modeling/least square support vector machine (LS-SVM)/multivariate molten iron quality引用本文复制引用
宋贺达,周平,王宏,柴天佑..高炉炼铁过程多元铁水质量非线性子空间建模及应用[J].自动化学报,2016,42(11):1664-1679,16.基金项目
国家自然科学基金(61473064,61290323,61333007),中央高校基本科研业务费项目(N130108001),辽宁省教育厅科技项目(L20150186)资助Supported by National Natural Science Foundation of China (61473064,61290323,61333007), the Fundamental Research Funds for the Central Universities (N130108001), the General Project on Scientific Research for the Education Department of Liaoning Province (L20150186) （61473064,61290323,61333007）
