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基于子空间方法的非均匀多采样率系统辨识
引用本文:王宏伟,孙爽. 基于子空间方法的非均匀多采样率系统辨识[J]. 大连理工大学学报, 2014, 54(5): 575-580
作者姓名:王宏伟  孙爽
作者单位:大连理工大学控制科学与工程学院
摘    要:针对非均匀多采样率系统的建模问题,根据因果关系,建立了非均匀多采样率系统的状态空间模型.对于含有提升变量的状态空间模型,提出基于子空间技术的辨识方法.首先,由系统的输入输出数据建立由Hankel矩阵组成的扩展状态空间方程;其次,利用斜交投影的原理,以及奇异值分解,通过子空间辨识算法确定增广观测矩阵和状态向量;最后,通过最小二乘方法确定模型的参数矩阵.该方法简单有效且对初值具有鲁棒性.仿真实例验证了方法的有效性.

关 键 词:非均匀多采样率系统  状态空间模型  子空间方法  系统辨识

Subspace-based method for identification of non-uniformly multirate sampling systems
WANG Hongwei,SUN Shuang. Subspace-based method for identification of non-uniformly multirate sampling systems[J]. Journal of Dalian University of Technology, 2014, 54(5): 575-580
Authors:WANG Hongwei  SUN Shuang
Affiliation:WANG Hong-wei;SUN Shuang;School of Control Science and Engineering,Dalian University of Technology;
Abstract:According to the modeling of non-uniformly multirate sampling system, a state space model is derived due to the casual relationship. Subspace-based identification is developed for state space models, which have lifting variables. Firstly, an extended state space equation formed by input-output Hankel matrices is established. Then, the extended observability matrices and state vectors are obtained by subspace-based identification algorithm through the oblique projection and singular value decomposition. Lastly, the parameter matrices are determined using the least square algorithm. A simulation example is presented to illustrate the performance and robustness for initials of the proposed method.
Keywords:non-uniformly multirate sampling system   state space model   subspace-based method   system identification
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