Robust Gradient Estimation Algorithm for a Stochastic System with Colored Noise

被引：36

作者：

Liu, Wentao ^{[1
]}

Xiong, Weili ^{[1
]}

机构：

[1] Jiangnan Univ, Sch Internet Things Engn, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China

来源：

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2023年 / 21卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Continuous mixed p-norm; gradient search; multi-innovation identification; parameter estimation; PARAMETER-ESTIMATION; OUTPUT ESTIMATION; BILINEAR-SYSTEMS; IDENTIFICATION;

D O I：

10.1007/s12555-021-0572-4

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper studies the parameter estimation algorithms of a finite impulse response system with colored noise. To suppress the negative effects of the colored noises, a novel gradient-based algorithm is developed by means of the cost function of the continuous mixed p-norm (CMPN). It combines the p-norms for 1 <= p <= 2, which control the proportions of the error norms and generate an adjustable gain to adapt the data quality. Moreover, to improve the convergence rate, a CMPN multi-innovation gradient recursive algorithm is derived through expanding the innovation scalar to the innovation vector. Finally, two examples are given to demonstrate the validity of the proposed algorithms.

引用

页码：553 / 562

页数：10

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