Hierarchical Stochastic Gradient Algorithm and its Performance Analysis for a Class of Bilinear-in-Parameter Systems

被引：0
作者：
Feng Ding
Xuehai Wang
机构：
[1] Nanchang Hangkong University,School of Information Engineering
[2] Xinyang Normal University,College of Mathematics and Information Science
来源：
Circuits, Systems, and Signal Processing | 2017年 / 36卷
关键词：
Parameter estimation; Gradient search; Hierarchical identification; Performance analysis; Bilinear-in-parameter system;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper considers the parameter identification for a special class of nonlinear systems, i.e., bilinear-in-parameter systems. Based on the hierarchical identification principle, a hierarchical stochastic gradient (HSG) estimation algorithm is presented. The basic idea is to decompose a bilinear-in-parameter system into two subsystems and to derive the HSG identification algorithm for estimating the system parameters by replacing the unknown variables in the information vectors with their estimates obtained at the previous time. The convergence analysis of the proposed algorithm indicates that the parameter estimation errors converge to zero under persistent excitation conditions. The simulation results show that the proposed algorithm is effective.
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收藏
页码：1393 / 1405
页数：12
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