基于组合信号源的非线性系统的子空间辨识
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TN911.7

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国家自然科学基金(No.61863034)第一作者:侯玉雯(1994—),女,汉,山西省孝义市人,硕士研究生。研究方向:非线性系统辨识。E-mail:1059826381@qq.com。*通信作者:王宏伟(1969—),男,汉,吉林省长春市人,博士,教授。研究方向:非线性系统辨识。E-mail:1195201627@qq.com。 .Department of School of electrical engineering, Xinjiang University, Urumqi, 830047, China; 2.School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China)


Subspace Identification of Nonlinear Systems Based on Hybrid Signal Sources
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    摘要:

    本文提出了基于组合信号源的辨识方法,目的在于解决对非线性采样系统的状态空间Hammerstein模型难以辨识的问题,。首先用组合信号源将静态非线性环节和动态线性环节分离。其次,采用模糊神经模型拟合静态非线性环节,这样有效地避免了采用多项式方法逼近非线性函数的限制,拓宽了非线性模型的适用范围;采用子空间算法估计采样系统的状态空间参数矩阵。最后,通过对两个非线性Hammerstein系统模型的仿真,验证了本文方法的准确性和有效性。

    Abstract:

    In this paper, an identification method based on combined signal sources is proposed to solve the difficult identification problem of state space Hammerstein model for nonlinear sampling systems.Firstly, the static nonlinear part and the dynamic linear part were separated by the hybrid signal source. Secondly, the neural fuzzy model was used to approach to the static nonlinear part, which effectively avoided the limitation of approaching the nonlinear function by polynomial method and broadened the applicable scope of the nonlinear model. In addition, the subspace algorithm was used to estimate the state space parameter matrix of the sampling system.Finally, the accuracy and effectiveness of the proposed method were verified by simulation of two nonlinear Hammerstein system models.

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侯玉雯,王宏伟. 基于组合信号源的非线性系统的子空间辨识[J]. 科学技术与工程, 2021, 21(10): 4084-4091.
Hou Yuwen, Wang Hongwei. Subspace Identification of Nonlinear Systems Based on Hybrid Signal Sources[J]. Science Technology and Engineering,2021,21(10):4084-4091.

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  • 收稿日期:2020-07-13
  • 最后修改日期:2021-01-06
  • 录用日期:2020-12-04
  • 在线发布日期: 2021-04-28
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