Identification for Hammerstein nonlinear ARMAX systems based on multi-innovation fractional order stochastic gradient

被引：69

作者：

Cheng, Songsong ^{[1
]}

Wei, Yiheng ^{[1
]}

Sheng, Dian ^{[1
]}

Chen, Yuquan ^{[1
]}

Wang, Yong ^{[1
]}

机构：

[1] Univ Sci & Technol China, Dept Automat, Hefei 230027, Anhui, Peoples R China

来源：

SIGNAL PROCESSING | 2018年 / 142卷

基金：

中国国家自然科学基金; 中国博士后科学基金;

关键词：

Fractional order calculus; Hammerstein nonlinear ARMAX systems; MIFOSG; Identification; Convergence; PARAMETER-ESTIMATION; ADAPTIVE STRATEGY; LINEAR-SYSTEMS; KALMAN FILTER; ALGORITHMS;

D O I：

10.1016/j.sigpro.2017.06.025

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A multi-innovation fractional order stochastic gradient (MIFOSG) algorithm, which involves a variable initial value scheme, is investigated to identify the Hammerstein nonlinear ARMAX systems in this paper. Firstly, according to an improved fractional order gradient method, the MIFOSG algorithm is proposed. Furthermore, according to the martingale convergence theorem, the convergence analysis of the proposed algorithm is developed. In addition, for the purpose of improving the convergence performance, a forgetting factor on step size and a variable gradient order are introduced. Given a sufficiently large number of independent runs, the effectiveness of the proposed algorithm is demonstrated in two numerical examples finally. (C) 2017 Published by Elsevier B.V.

引用

页码：1 / 10

页数：10

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