Gradient estimation algorithms for the parameter identification of bilinear systems using the auxiliary model

For the bilinear system with white noise, the difficulty of identification is that there exists the product term of the state and input in the system. To overcome this difficulty, we derive the input–output representation of a class of special bilinear systems by using the transformation, and presen...

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Bibliographic Details
Published in:Journal of computational and applied mathematics 2020-05, Vol.369, p.112575, Article 112575
Main Authors: Ding, Feng, Xu, Ling, Meng, Dandan, Jin, Xue-Bo, Alsaedi, Ahmed, Hayat, Tasawar
Format: Article
Language:English
Subjects:
Bilinear system
Gradient search
Iterative algorithm
Measurement information
Parameter estimation
State space system
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Summary:For the bilinear system with white noise, the difficulty of identification is that there exists the product term of the state and input in the system. To overcome this difficulty, we derive the input–output representation of a class of special bilinear systems by using the transformation, and present a stochastic gradient (SG) algorithm and a gradient-based iterative algorithm for estimating the parameters of the systems in the case of the known input–output data by means of the auxiliary model. The proposed gradient-based iterative algorithm can generate more accurate parameter estimates than the auxiliary model based SG algorithm. The performance of the proposed algorithms are tested by two numerical examples.
ISSN:0377-0427
1879-1778
DOI:10.1016/j.cam.2019.112575