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- Title
Gradient‐based iterative parameter estimation for bilinear‐in‐parameter systems using the model decomposition technique.
- Authors
Chen, Mengting; Ding, Feng; Yang, Erfu
- Abstract
The parameter estimation issues of a block‐oriented non‐linear system that is bilinear in the parameters are studied, i.e. the bilinear‐in‐parameter system. Using the model decomposition technique, the bilinear‐in‐parameter model is decomposed into two fictitious submodels: one containing the unknown parameters in the non‐linear block and the other containing the unknown parameters in the linear dynamic one and the noise model. Then a gradient‐based iterative algorithm is proposed to estimate all the unknown parameters by formulating and minimising two criterion functions. The stochastic gradient algorithms are provided for comparison. The simulation results indicate that the proposed iterative algorithm can give higher parameter estimation accuracy than the stochastic gradient algorithms.
- Publication
IET Control Theory & Applications (Wiley-Blackwell), 2018, Vol 12, Issue 17, p2380
- ISSN
1751-8644
- Publication type
Article
- DOI
10.1049/iet-cta.2018.5254