引用本文:贾文君,柴天佑.稀土串级萃取分离过程的双线性模型及其参数辨识[J].控制理论与应用,2006,23(5):717~723.[点击复制]
JIA Wen-jun, CHAI Tian-you .Bilinear model of rare earth cascade extraction process and its parameter identification[J].Control Theory and Technology,2006,23(5):717~723.[点击复制]
稀土串级萃取分离过程的双线性模型及其参数辨识
Bilinear model of rare earth cascade extraction process and its parameter identification
摘要点击 1686  全文点击 708  投稿时间：2005-05-24  修订日期：2005-11-23
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DOI编号  10.7641/j.issn.1000-8152.2006.5.010
  2006,23(5):717-723
中文关键词  稀土串级萃取  双线性模型  参数辨识
英文关键词  rare earth cascade extraction  bilinear model  parameter identification
基金项目  国家重点基础研究发展计划(973)项目(2002CB312201); 国家自然科学基金重点项目(60534010); 国家创新研究群体科学基金项目(60521003); 长江学者和创新团队发展计划资助(IRT0421)．
作者单位
贾文君,柴天佑 东北大学自动化研究中心,辽宁沈阳110004 
中文摘要
      稀土串级萃取分离过程元素组分含量的在线检测对于提高金属直收率至关重要,由于难以实现连续在线测量,因此研究动态模型成为采用软测量技术的关键．本文以稀土串级萃取分离过程的物料平衡方程为基础,提出了一种具有状态滞后的双线性动态模型,并对模型进行了分段集结降阶简化．通过工业现场采集的数据,采用最小二乘法对模型参数进行辨识,并根据误差指标选择最佳系统时滞,得到了表征稀土串级萃取分离过程的动态数学模型．稀土串级萃取分离过程实际数据的仿真结果表明了该建模方法的有效性和模型的准确性．
英文摘要
      In the process of rare earth cascade extraction, the online measurement of element component content is extremely important to improve the direct recovery of metals. Because of the difficulty of implementing online measurement, research on the dynamical model becomes the key problem in soft-sensor technology. In this paper, based on the material balance equations in the process of rare earth cascade extraction, a bilinear model with time-delay is proposed. The established model is also simplified by reducing its order. The recursive least-squares identification method is then adopted to identify the model parameters by using the data selected in an industrial field. The optimal time delay constant is simultaneously selected according to the error index. The mathematical model representing the rare earth cascade extraction process is thus obtained. Finally, simulations are conducted by using the practical data from the rare earth cascade extraction process, and the results show the effectiveness of the modeling method and the validity of the model.