Subspace identification of closed loop systems by the orthogonal decomposition method
Subspace identification of closed loop systems by the orthogonal decomposition method
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DOI：
10.1016/j.automatica.2004.11.026
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发表时间：
2005-05
期刊：
影响因子：
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通讯作者：
T. Katayama;H. Kawauchi;G. Picci
中科院分区：
文献类型：
--
作者：
T. Katayama;H. Kawauchi;G. Picci
本文考虑了应用信号处理的随机实现技术来辨识闭环系统的确定性部分的问题。52（2）（1996）145）。使用一个初步的正交分解，该问题被减少到确定的联合输入输出过程的确定性组件的基础上确定的植物和控制器。讨论了输入信号在闭环辨识中的作用及基于有限数据的实现方法，并给出了辨识被控对象和控制器状态空间模型的子空间方法。由于得到的模型是高阶的，模型降阶过程应适用于推导低阶模型。一些数值结果表明，本技术的适用性。
In this paper, we consider a problem of identifying the deterministic part of a closed loop system by applying the stochastic realization technique of (Signal Process. 52 (2) (1996) 145) in the framework of the joint input–output approach. Using a preliminary orthogonal decomposition, the problem is reduced to that of identifying the plant and controller based on the deterministic component of the joint input–output process. We discuss the role of input signals in closed loop identification and the realization method based on a finite data, and then sketch a subspace method for identifying state space models of the plant and controller. Since the obtained models are of higher order, a model reduction procedure should be applied for deriving lower order models. Some numerical results are included to show the applicability of the present technique.