Impulse response function identification of linear mechanical systems based on Kautz basis expansion with multiple poles

Changming Cheng, Zhike Peng, Xingjian Dong, Wenming Zhang and Guang Meng

International Journal of Systems Science, 2018, vol. 49, issue 7, 1559-1571

Abstract: The impulse response function (IRF) identification of linear mechanical systems is important in many engineering applications. This paper proposes a novel IRF identification method of linear systems based on Kautz basis expansion with multiple poles. In order to reduce the parameters to be identified, the IRF is expanded in terms of orthogonal Kautz functions with multiple poles, and the poles in Kautz functions should be optimised. This allows the identification of IRF for linear mechanical systems operated under more than one mode, such as systems under the white noise excitation or the swept frequency excitation with a wide range of frequency, and can improve the identification accuracy. Furthermore, based on the backpropagation through-time technique and the expectation maximisation algorithm, a pole optimisation algorithm is presented in this paper. The simulation studies verify the effectiveness of the proposed IRF identification method.

Date: 2018
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DOI: 10.1080/00207721.2018.1463408

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