引用本文:肖德云, 牛邵华.一种可以同时辨识模型参数和阶次的辅助变量法[J].控制理论与应用,1988,5(2):69~77.[点击复制]
Xiao Deyun, Niu Shaohua.An Implementation of the Instrumental Variable Method for Simultaneous Identification of Model Order and Parameters[J].Control Theory and Technology,1988,5(2):69~77.[点击复制]
一种可以同时辨识模型参数和阶次的辅助变量法
An Implementation of the Instrumental Variable Method for Simultaneous Identification of Model Order and Parameters
摘要点击 832  全文点击 383  投稿时间:1987-05-15  修订日期:1987-10-16
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DOI编号  
  1988,5(2):69-77
中文关键词  
英文关键词  
基金项目  
作者单位
肖德云, 牛邵华 清华大学自动化系 
中文摘要
      在用辅助变量法对SISO线性模型进行辨识时,如果将其数据向量和辅助向量重新排列并扩维,利用由此而出现的“移位性质”,则可构成一种新的数据乘积矩阵,其逆矩阵称作信息压缩阵。本文提出一种新的UDVT分解方法,并利用它对这个信息压缩阵进行递推分解,构成了一种能同时进行模型参数和阶次辨识的递推算法。使用这种新的辨识算法,可以减小整个辨识过程的计算量,改善数值计算品质,提高辨识精度。
英文摘要
      The paper has presented an implementation of the instrumental variable method which can be used in simultaneous identification of the model order and parameters. By extension and rearrangement of the data vectors in the IV algorithm, a covariance matrix called the Condensed Information Matrix(CIM), which is nonsymmetric, can be constructed. Applying the UDVT factorization technique to the matrix, the model order and parameters can be obtained simultaneously. This identification method is superior to the conventional IV method when the model order is high. Our algorithm has better in accuracy and requires less computational efforts.