Generalizing Robust Control Barrier Functions From a Controller Design Perspective

Anil Alan;Tamas G. Molnar;Aaron D. Ames;Gábor Orosz
{"title":"Generalizing Robust Control Barrier Functions From a Controller Design Perspective","authors":"Anil Alan;Tamas G. Molnar;Aaron D. Ames;Gábor Orosz","doi":"10.1109/OJCSYS.2025.3529364","DOIUrl":null,"url":null,"abstract":"While control barrier functions provide a powerful tool to endow controllers with formal safety guarantees, robust control barrier functions (RCBF) can be used to extend these guarantees for systems with model inaccuracies. This paper presents a generalized RCBF framework that unifies and extends existing notions of RCBFs for a broad class of model uncertainties. Main results are conditions for robust safety through generalized RCBFs. We apply these generalized principles for more specific design examples: a worst-case type design, an estimation-based design, and a tunable version of the latter. These examples are demonstrated to perform increasingly closer to an oracle design with ideal model information. Theoretical contributions are demonstrated on a practical example of a pendulum with unknown periodic excitation. Using numerical simulations, a comparison among design examples are carried out based on a performance metric depicting the increased likeness to the oracle design.","PeriodicalId":73299,"journal":{"name":"IEEE open journal of control systems","volume":"4 ","pages":"54-69"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10839547","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE open journal of control systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10839547/","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

While control barrier functions provide a powerful tool to endow controllers with formal safety guarantees, robust control barrier functions (RCBF) can be used to extend these guarantees for systems with model inaccuracies. This paper presents a generalized RCBF framework that unifies and extends existing notions of RCBFs for a broad class of model uncertainties. Main results are conditions for robust safety through generalized RCBFs. We apply these generalized principles for more specific design examples: a worst-case type design, an estimation-based design, and a tunable version of the latter. These examples are demonstrated to perform increasingly closer to an oracle design with ideal model information. Theoretical contributions are demonstrated on a practical example of a pendulum with unknown periodic excitation. Using numerical simulations, a comparison among design examples are carried out based on a performance metric depicting the increased likeness to the oracle design.
从控制器设计的角度推广鲁棒控制屏障函数
虽然控制屏障函数提供了一个强大的工具,赋予控制器正式的安全保证,鲁棒控制屏障函数(RCBF)可用于扩展这些保证,以模型不准确的系统。本文提出了一个广义的RCBF框架,该框架统一并扩展了现有的RCBF概念,用于广泛的模型不确定性。主要结果是通过广义rcbf实现鲁棒安全性的条件。我们将这些广义原则应用于更具体的设计示例:最坏情况类型设计,基于估计的设计,以及后者的可调版本。这些示例的执行越来越接近具有理想模型信息的oracle设计。通过一个具有未知周期激励的钟摆实例,证明了理论贡献。通过数值模拟,基于性能指标对设计实例进行了比较,该指标描述了与oracle设计的相似性增加。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信