Gradient-Based Iterative Identification for Wiener Nonlinear Dynamic Systems with Moving Average Noises
School of Electrical and Automatic Engineering, Changshu Institute of Technology, Hushan RoadNo.99, Changshu 215500, China
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Academic Editor: Alicia Cordero
Algorithms 2015, 8(3), 712-722; https://doi.org/10.3390/a8030712
Received: 30 June 2015 / Revised: 20 July 2015 / Accepted: 20 August 2015 / Published: 26 August 2015
(This article belongs to the Special Issue Numerical Algorithms for Solving Nonlinear Equations and Systems)
This paper focuses on the parameter identification problem for Wiener nonlinear dynamic systems with moving average noises. In order to improve the convergence rate, the gradient-based iterative algorithm is presented by replacing the unmeasurable variables with their corresponding iterative estimates, and to compute iteratively the noise estimates based on the obtained parameter estimates. The simulation results show that the proposed algorithm can effectively estimate the parameters of Wiener systems with moving average noises.
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Keywords:
nonlinear dynamic system; stochastic gradient; iterative algorithm; output error moving average; parameter estimation
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MDPI and ACS Style
Zhou, L.; Li, X.; Xu, H.; Zhu, P. Gradient-Based Iterative Identification for Wiener Nonlinear Dynamic Systems with Moving Average Noises. Algorithms 2015, 8, 712-722.
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