System realization using information matrix
System realization using information matrix
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DOI：
10.2514/2.4068
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发表时间：
1997-05-01
影响因子：
2.6
通讯作者：
Juang, JN
中科院分区：
文献类型：
--
作者：
Juang, JN
介绍了由移位输入输出数据的自相关矩阵和互相关矩阵组成的广义信息矩阵。基于数据关联的概念，提出了一种直接从输入输出数据中识别模型的系统实现算法。该算法首先计算信息矩阵，得到一个特殊的相关矩阵，进而得到系统的可观测性矩阵和状态向量相关。然后，可以结合其他代数操作，从可观察性矩阵中识别出系统模型。该算法导致了几种不同的计算系统矩阵的方法来表示系统模型。最后给出了一个实验实例，并进行了比较，说明了这些方法的有效性和实用性。
A generalized version of the information matrix is introduced consisting of the autocorrelation and cross correlation matrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm is developed to identify a model directly from input and output data. The algorithm starts with computing the information matrix to derive a special correlation matrix that in turn produces the system observability matrix and the state-vector correlation. A system model can then be identified from the observability matrix in conjunction with other algebraic manipulations. The algorithm leads to several different methods for computing system matrices to represent the system model. An experimental example is given to illustrate the validity and usefulness of these methods with some comparison.