System identification based on Hammerstein model
System identification based on Hammerstein model
复制标题
DOI：
10.1080/00207170500096666
复制
发表时间：
2005-04
影响因子：
2.1
通讯作者：
F. Chaoui;F. Giri;Y. Rochdi;M. Haloua;A. Naitali
中科院分区：
文献类型：
--
作者：
F. Chaoui;F. Giri;Y. Rochdi;M. Haloua;A. Naitali
我们正在考虑基于Hammerstein模型的非线性系统识别，即与线性动态串联的非线性静态增益。静态增益特性是任何非线性函数F。设计了一种辨识方案，以获得设备动态模型和一组N个不同点（x，F（x））的估计，其中N由用户任意选择。这种方案涉及最小二乘和预测误差算法以及代数变换，如奇异值分解（SVD）。有趣的是，所提出的方案确保持续激励，从而允许在没有外部干扰的情况下精确的模型识别。
We are considering non-linear system identification based on the Hammerstein model i.e. a non-linear static gain in series with linear dynamics. The static gain characteristic is any non-linear function F. An identification scheme is designed to get estimates of both the plant dynamics model and a set of N different points (x, F(x)), where N is arbitrarily chosen by the user. Such a scheme involves least squares and prediction-error algorithms as well as algebraic transformations such as singular values decomposition (SVD). Interestingly, the proposed scheme ensures persistent excitation allowing thus exact model identification in the case of no external disturbances.