COMPARISONS OF SUBSPACE IDENTIFICATION METHODS FOR SYSTEMS OPERATING ON CLOSED-LOOP
COMPARISONS OF SUBSPACE IDENTIFICATION METHODS FOR SYSTEMS OPERATING ON CLOSED-LOOP
复制标题
闭环系统子空间识别方法比较
DOI：
10.3182/20050703-6-cz-1902.00083
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
L. Ljung
中科院分区：
文献类型：
--
作者：
Weilu Lin;S. Joe Qin;L. Ljung
在本文中，我们分析了最近提出的两种闭环子空间识别方法，分别称为创新估计方法和白化滤波器方法。详细研究了它们之间的相似性和差异。事实证明，所有闭环子空间识别方法都可以分为一步、两步或多级投影方法。 SISO 闭环仿真表明，为了识别一致的模型，白化滤波器方法可能需要比创新估计方法更长的未来和过去视野。
In this paper, we analyze two recently proposed closed-loop subspace identification methods, referred to as innovation estimation method and whitening filter approach respectively. The similarity and difference between them are investigated in detail. It turns out that all closed-loop subspace identification methods can be classified as one-step, two-step, or multi-stage projection methods. A SISO closed-loop simulation shows that to identify a consistent model the whitening filter approach might require longer future and past horizons than the innovation estimation method.