Enhancing slow-sampled loops in input multi-rate digital tracking control systems: An overview

In error-based tracking control systems and reference signal tracking systems, the dynamic performance of slow-sampled loops is often inferior to that of fast-sampled loops. This paper focuses on the challenges encountered in such systems when performing error-based tracking tasks and reviews the methods proposed in the literature to address these issues. In particular, it examines how slow-sampled image sequences can be effectively treated as fast-sampled signals for closed-loop tracking, and how efficient and robust control strategies can be designed using slow-sampling sensor data. This paper provides an overview of the framework for input multi-rate digital tracking control systems and presents a comprehensive review, highlighting two research directions aimed at improving the performance of slow-sampled loops and addressing inherent challenges. Finally, it critically evaluates the applicability of these research directions and discusses their limitations as well as opportunities for future investigation.

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Publication Details

Journal
Transactions of the Institute of Measurement and Control
Published
2026-03-21
DOI
https://doi.org/10.1177/01423312261428512
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing slow-sampled loops in input multi-rate digital tracking control systems: An overview

Qianwen Duan, Luyao Zhang, Jincong Zhu, Qiliang Bao et al.
Transactions of the Institute of Measurement and Control
Target Tracking and Data Fusion in Sensor Networks
article

Enhancing slow-sampled loops in input multi-rate digital tracking control systems: An overview

Qianwen Duan, Luyao Zhang, Jincong Zhu, Qiliang Bao, Shanlin Zhuang, Yao Mao
article en

Abstract

In error-based tracking control systems and reference signal tracking systems, the dynamic performance of slow-sampled loops is often inferior to that of fast-sampled loops. This paper focuses on the challenges encountered in such systems when performing error-based tracking tasks and reviews the methods proposed in the literature to address these issues. In particular, it examines how slow-sampled image sequences can be effectively treated as fast-sampled signals for closed-loop tracking, and how efficient and robust control strategies can be designed using slow-sampling sensor data. This paper provides an overview of the framework for input multi-rate digital tracking control systems and presents a comprehensive review, highlighting two research directions aimed at improving the performance of slow-sampled loops and addressing inherent challenges. Finally, it critically evaluates the applicability of these research directions and discusses their limitations as well as opportunities for future investigation.

Transactions of the Institute of Measurement and Control
University of Electronic Science and Technology of China (CN), Chinese Academy of Sciences (CN), Institute of Optics and Electronics, Chinese Academy of Sciences (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 15%
Target Tracking and Data Fusion in Sensor Networks
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