Closed-loop MOESP subspace model identification with parametrisable disturbances
Closed-loop MOESP subspace model identification with parametrisable disturbances
复制标题
具有参数化扰动的闭环 MOESP 子空间模型识别
DOI：
10.1109/cdc.2010.5717872
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
M. Verhaegen
中科院分区：
文献类型：
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作者：
G. Veen;J. Wingerden;M. Verhaegen
本文提出了一种新的开环和闭环系统的子空间辨识方法。该方法通过对测量数据进行RQ因子分解来获得新息序列的估计，从而避免了显式求解最小二乘问题。在第二步中，估计的新息序列用于执行普通MOESP [1]以找到系统矩阵直到相似性变换。闭环识别算法也适用于存在某些干扰输入的情况，这些干扰输入可以根据合适的基函数进行参数化。所有的计算都是使用数据的正交因式分解进行的。该方法是通过将其应用到一个系统的闭环操作和测量周期性干扰的真实的系统。
A new subspace identification method for systems operating either in open-loop or in closed-loop is presented. The method obtains an estimate of the innovation sequence by performing an RQ-factorization of the measurement data, thereby avoiding explicitly solving a least-squares problem. In a second step, the estimated innovation sequence is used to perform ordinary MOESP [1] to find the system matrices up to a similarity transformation. The closed-loop identification algorithm also applies to cases where certain disturbance inputs are present that can be parametrised in terms of suitable basis functions. All computations are performed using orthogonal factorisations of the data. The method is illustrated by applying it to a system operating in closed-loop and to measurements from a real system with periodic disturbances.
闭环运行的 LTI 系统的直接子空间模型识别
DOI：
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发表时间：
2005
期刊：
Proceedings of the 43^<rd> IEEE Conference on Decision and Control
影响因子：
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作者：
Hiroshi Oku;Takao Fujii
通讯作者：
Takao Fujii