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Continuous-time MISO fractional system identification using higher-order-statistics.
- Source :
- Fractional Calculus & Applied Analysis; Aug2024, Vol. 27 Issue 4, p1611-1638, 28p
- Publication Year :
- 2024
-
Abstract
- In this paper, the problem of identifying Multiple-Input-Single-Output (MISO) systems with fractional models from noisy input-output available data is studied. The proposed idea is to use Higher-Order-Statistics (HOS), like fourth-order cumulants (foc), instead of noisy measurements. Thus, a fractional fourth-order cumulants based-simplified and refined instrumental variable algorithm (frac-foc-sriv) is first developed. Assuming that all differentiation orders are known a priori, it consists in estimating the linear coefficients of all Single-Input-Single-Output (SISO) sub-models composing the MISO model. Then, the frac-foc-sriv algorithm is combined with a nonlinear optimization technique to estimate all the parameters: coefficients and orders. The performances of the developed algorithms are analyzed using numerical examples. Thanks to fourth-order cumulants, which are insensitive to Gaussian noise, and the iterative strategy of the instrumental variable algorithm, the parameters estimation is consistent. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13110454
- Volume :
- 27
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- Fractional Calculus & Applied Analysis
- Publication Type :
- Academic Journal
- Accession number :
- 178504289
- Full Text :
- https://doi.org/10.1007/s13540-024-00297-x