Data-Based Encryption Iterative Learning Heading Control for Unmanned Surface Vehicles

被引：0

作者：

Chen, Chen ^{[1
]}

Zhao, Huarong ^{[1
]}

Shan, Jinjun ^{[2
]}

Yu, Hongnian ^{[3
]}

机构：

[1] Jiangnan Univ, Engn Res Ctr Internet Things Applicat, Minist Educ, Wuxi 214122, Jiangsu, Peoples R China

[2] York Univ, Dept Earth & Space Sci & Engn, Toronto, ON M3J 1P3, Canada

[3] Edinburgh Napier Univ, Sch Comp Engn & Built Environm, Edinburgh EH10 5DT, Scotland

来源：

IEEE CONTROL SYSTEMS LETTERS | 2025年 / 9卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

Control systems; Adaptation models; Encryption; Decoding; Privacy; Data models; Convergence; Autonomous vehicles; Angular velocity; Vehicle dynamics; Unmanned surface vehicles; data-driven control; heading control; iteration learning; encrypted data;

D O I：

10.1109/LCSYS.2025.3578918

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 letter investigates a data-driven iterative learning heading control problem for unmanned surface vehicles (USVs) with encoding-decoding mechanisms. First, a compact form dynamic linearized model of the USV is established using dynamic linearization techniques and redefined outputs. Then, an encoding-decoding scheme is designed, which encodes the data before transmission and decodes the data received by the controller. This strategy compresses the data and offers protection from potential breaches of information. Finally, the convergence of the designed method is theoretically analyzed, and simulation results demonstrate its effectiveness in enhancing heading control performance.

引用

页码：973 / 978

页数：6

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