| 引用本文: | 桂卫华,宋海鹰,阳春华.Hammerstein-Wiener模型最小二乘向量机辨识及其应用[J].控制理论与应用,2008,25(3):393~397.[点击复制] |
| GUI Wei-hua,SONG Hai-ying,YANG Chun-hua.Hammerstein-Wiener model identified by least-squares-support-vector machine and its application[J].Control Theory and Technology,2008,25(3):393~397.[点击复制] |
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| Hammerstein-Wiener模型最小二乘向量机辨识及其应用 |
| Hammerstein-Wiener model identified by least-squares-support-vector machine and its application |
| 摘要点击 1957 全文点击 2271 投稿时间：2007-03-14 修订日期：2007-09-12 |
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| DOI编号 10.7641/j.issn.1000-8152.2008.3.002 |
| 2008,25(3):393-397 |
| 中文关键词 Hammerstein-Wiener模型 最小二乘向量机 系统辨识 智能建模 铜转炉吹炼预测 |
| 英文关键词 Hammerstein-Wiener model least squares vector machine system identification intelligence model copper converting prediction |
| 基金项目 国家自然科学基金资助项目(60634020,60574030); 国家重点基础研究发展规划资助项目(2002cb312200); 博士点基金资助项目(20050533016). |
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| 中文摘要 |
| 借鉴最小二乘支持向量机求解的思路, 文中提出了辨识多输入–单输出Hammerstein-Wiener模型的方法.引入共线性约束假设, 将辨识问题转换为有约束的优化问题, 从而辨识出Hammerstein-Wiener模型的参数. 基于Hammerstein-Wiener模型, 我们建立了一个多输入–单输出的滚动预测模型, 对铜转炉造渣S2期吹炼所需总氧量进行了预测, 其相对均方根误差为12.1%. 仿真结果表明, 该模型预测准确、具有较好的应用价值. |
| 英文摘要 |
| The identification method for a multi-input single-output Hammerstein-Wiener model is proposed by using the solving method of the least-squares-support-vector machine. The identification problem is converted into a constrained optimization problem by assuming collinear constraints so that the parameters of Hammerstein-Wiener model can be identified. Based on the Hammerstein-Wiener model, a multi-input single-output receding-horizon prediction model is developed for predicting the total oxygen quantity required by a copper converter in slag making S2 stage. The relative root-meansquare error (RRMSE) is 12.1%. The simulation research shows that this model provides accurate prediction and is with desirable application value. |