Momentum Stochastic Gradient Algorithm With Data Filtering for Generalized Time‐Varying Systems

Optimal Control Applications and Methods 2026

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Authors: Kai Yao, Yan Ji, Hao Fang
DOI: 10.1002/oca.70109
Cited by: 4
References: 121

Abstract

ABSTRACT This article proposes an accelerated gradient‐based parameter estimation for generalized time‐varying systems. A momentum term is incorporated into the parameter adaptation law to accelerate convergence and suppress oscillatory behavior. In addition, the data filtering technique is applied to preprocess the input and output signals, effectively attenuating the influence of colored noise on parameter estimation. The proposed algorithm is further validated through its application to a DC motor system.

Fields of Study & Subjects

Advanced Adaptive Filtering Techniques Control Systems and Identification Stability and Control of Uncertain Systems

Publication details

Journal / source
Optimal Control Applications and Methods
Publisher
Wiley
Volume
47
Issue
4
Pages
989–1003
Publication date
10 June 2026
Language
EN