Active disturbance rejection control for a quadrotor: a high-gain observer-based sliding-mode technique

Ming Du, Yue-Xiang Shi, Jing Zhao, Chongxing Liu
{"title":"Active disturbance rejection control for a quadrotor: a high-gain observer-based sliding-mode technique","authors":"Ming Du, Yue-Xiang Shi, Jing Zhao, Chongxing Liu","doi":"10.1109/ISAS59543.2023.10164394","DOIUrl":null,"url":null,"abstract":"This study is investigates the trajectory tracking control problem of a quadrotor unmanned aerial vehicle (UAV). To ensure desired trajectory tracking performance despite modeled uncertainty and external gust interference, an active disturbance rejection control (ADRC) strategy is proposed, which separates the UAV control system into two parts. The ADRC strategy is applied in the attitude control (AC) system to address internal system uncertainty and ensure dynamic performance. In the position control (PC) system, sliding-mode control (SMC) with a high-gain observer is introduced to guarantee system robustness against external and internal disturbances. The quadrotor system can converge the tracking error to an arbitrarily small set of residuals by constructing a Lyapunov function. Numerical analysis demonstrates that the proposed control system has good trajectory tracking and anti-disturbance performance for the quadrotor.","PeriodicalId":199115,"journal":{"name":"2023 6th International Symposium on Autonomous Systems (ISAS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 6th International Symposium on Autonomous Systems (ISAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAS59543.2023.10164394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This study is investigates the trajectory tracking control problem of a quadrotor unmanned aerial vehicle (UAV). To ensure desired trajectory tracking performance despite modeled uncertainty and external gust interference, an active disturbance rejection control (ADRC) strategy is proposed, which separates the UAV control system into two parts. The ADRC strategy is applied in the attitude control (AC) system to address internal system uncertainty and ensure dynamic performance. In the position control (PC) system, sliding-mode control (SMC) with a high-gain observer is introduced to guarantee system robustness against external and internal disturbances. The quadrotor system can converge the tracking error to an arbitrarily small set of residuals by constructing a Lyapunov function. Numerical analysis demonstrates that the proposed control system has good trajectory tracking and anti-disturbance performance for the quadrotor.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
四旋翼飞行器自抗扰控制:基于高增益观测器的滑模技术
研究了四旋翼无人机的轨迹跟踪控制问题。为了在模型不确定性和外部阵风干扰的情况下保证理想的轨迹跟踪性能,提出了一种将无人机控制系统分为两部分的自抗扰控制策略。将自抗扰策略应用于姿态控制系统,以解决系统内部的不确定性,保证系统的动态性能。在位置控制(PC)系统中,引入了带有高增益观测器的滑模控制(SMC),以保证系统对外部和内部干扰的鲁棒性。通过构造李雅普诺夫函数,四旋翼系统可以将跟踪误差收敛到任意小的残差集。数值分析表明,该控制系统对四旋翼飞行器具有良好的轨迹跟踪和抗干扰性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A new type of video text automatic recognition method and its application in film and television works H∞ state feedback control for fuzzy singular Markovian jump systems with constant time delays and impulsive perturbations MMSTP: Multi-modal Spatiotemporal Feature Fusion Network for Precipitation Prediction Digital twin based bearing fault simulation modeling strategy and display dynamics End-to-End Model-Based Gait Recognition with Matching Module Based on Graph Neural Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1