Journal
NONLINEAR DYNAMICS
Volume 84, Issue 2, Pages 1045-1053Publisher
SPRINGER
DOI: 10.1007/s11071-015-2548-5
Keywords
Parameter estimation; Least squares; Gradient search; Data filtering; Nonlinear system
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Funding
- National Natural Science Foundation of China [61273194]
- PAPD of Jiangsu Higher Education Institutions
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This paper considers the parameter estimation problems of Hammerstein-Wiener systems by using the data filtering technique. In order to improve the estimation accuracy, the data filtering-based recursive generalized extended least squares algorithm is derived. In order to improve the computational efficiency, the data filtering-based generalized extended stochastic gradient algorithm is derived for estimating the system parameters. Finally, the computational efficiency of the proposed algorithms is analyzed and compared. The simulation results indicate that the proposed algorithms can effectively estimate the parameters of Hammerstein-Wiener systems.
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