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Recursive Subspace Identification of Continuous-Time Systems Using Generalized Poisson Moment Functionals

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Abstract

A method for recursive subspace identification of continuous-time systems based on generalized Poisson moment functionals is proposed. Most of the existing subspace identification methods have concentrated mainly on the time-invariant discrete-time systems. The results of subspace identification methods are confined to the discrete-time cases, due to the difference on the construction of Hankel matrices. In addition, the time-invariant identification algorithms are not suitable for online identification cases. In order to solve the problems above, the time derivatives of Hankel matrices can be evaluated by generalized Poisson moment functionals, which provides a simple linear mapping for identification algorithm without the amplification of stochastic noises. The size of the data matrices is fixed a priori to fade the influence of old data to the updated data, which is a key to reduce computational burden and storage cost of recursive algorithms. The efficiency of the presented method is provided by comparing simulation results.

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Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (NSFC) (Nos. 62003082, 61773106, 61806079, U1808205), the Natural Science Foundation of Hebei Province (No. F2021501018), the China Postdoctoral Science Foundation under Grant (No. 2018M641939), and the Fundamental Research Funds for the Central Universities (No. N2023009).

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Authors and Affiliations

  1. School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China

    Miao Yu & Ge Guo

  2. College of Information Science and Engineering, Northeastern University, Shenyang, China

    Jianchang Liu

  3. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China

    Jianchang Liu & Ge Guo

  4. College of Engineering, Ocean University of China, Qingdao, China

    Wenle Zhang

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  1. Miao Yu
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Correspondence to Miao Yu.

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Yu, M., Liu, J., Guo, G. et al. Recursive Subspace Identification of Continuous-Time Systems Using Generalized Poisson Moment Functionals. Circuits Syst Signal Process 41, 1848–1868 (2022). https://doi.org/10.1007/s00034-021-01871-x

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