On Convergence of Fractional-Order Tracking Differentiators

IF 3.2 3区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Robust and Nonlinear Control Pub Date : 2025-05-28 DOI:10.1002/rnc.8067

Zu-Feng Zhang, Shou-Bo Jin, Zhi-Liang Zhao, Ze-Hao Wu

引用次数: 0

Abstract

This paper investigates the convergence of nonlinear fractional-order tracking differentiators employing Caputo derivatives. Despite their significance, the convergence of fractional-order tracking differentiators has not been rigorously established to date. This paper addresses the gap in existing convergence proofs and offers a rigorous demonstration of the fractional-order tracking differentiators utilizing Caputo derivatives. Examples and numerical simulations are conducted to validate the effectiveness of the proposed results.

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分数阶跟踪微分器的收敛性

利用卡普托导数研究了非线性分数阶跟踪微分器的收敛性。尽管具有重要意义，分数阶跟踪微分器的收敛性至今尚未得到严格的建立。本文解决了现有收敛性证明的不足，并利用卡普托导数给出了分数阶跟踪微分器的严格证明。通过算例和数值仿真验证了所提结果的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Robust and Nonlinear Control 工程技术-工程：电子与电气

CiteScore

6.70

自引率

20.50%

发文量

505

审稿时长

2.7 months

期刊介绍： Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.