Denoising identification for nonlinear systems with distorted streaming
- Publication Type:
- Journal Article
- Citation:
- International Journal of Non-Linear Mechanics, 2019, 117
- Issue Date:
- 2019-12-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 1-s2.0-S0020746219302033-main.pdf | Published Version | 3.34 MB |
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© 2019 Elsevier Ltd Streaming usually happens in systems with asymmetric nonlinearity. It is a dynamic phenomenon that the midpoint of the motion shifts away from the equilibrium point of the system. It is also an ultra-low-frequency process so that its observation often distorts because of signal acquisition limitations. Extensive studies have shown that the precision of parameter identification will drop greatly if this distortion is not accurately corrected. Motivated by the intention of enhancing the parameter identification's precision via signal correction, the present paper proposes a novel approach called the orthonormal Legendre polynomial based denoising identification method (OLP-DIM). In this method, the distorted response is decomposed by the orthonormal Legendre polynomials. The polynomial coefficients corresponding to the distortion are treated as uncertain parameters and then jointly identified with the system parameters. Numerical and experimental examples with different responses show that the OLP-DIM returns parameters in excellent precision and, distinct from traditional parameter identification methods, accurately recovers the system's streaming.
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