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基于滤波控制障碍函数的严格反馈系统安全控制

陈仲秋 刘勇华 苏春翌

陈仲秋, 刘勇华, 苏春翌. 基于滤波控制障碍函数的严格反馈系统安全控制. 自动化学报, 2024, 50(12): 1−13 doi: 10.16383/j.aas.c240003
引用本文: 陈仲秋, 刘勇华, 苏春翌. 基于滤波控制障碍函数的严格反馈系统安全控制. 自动化学报, 2024, 50(12): 1−13 doi: 10.16383/j.aas.c240003
Chen Zhong-Qiu, Liu Yong-Hua, Su Chun-Yi. Safe control of strict-feedback systems using filtered control barrier functions. Acta Automatica Sinica, 2024, 50(12): 1−13 doi: 10.16383/j.aas.c240003
Citation: Chen Zhong-Qiu, Liu Yong-Hua, Su Chun-Yi. Safe control of strict-feedback systems using filtered control barrier functions. Acta Automatica Sinica, 2024, 50(12): 1−13 doi: 10.16383/j.aas.c240003

基于滤波控制障碍函数的严格反馈系统安全控制

doi: 10.16383/j.aas.c240003
基金项目: 国家自然科学基金(62173097, U2013601), 广东省基础与应用基础研究基金面上项目(2022A515011239), 广东省特支计划本土创新创业项目(2019BT02X353) 资助
详细信息
    作者简介:

    陈仲秋:广东工业大学自动化学院博士研究生. 主要研究方向为非线性系统安全分析与控制. E-mail: 1112104010@mail2.gdut.edu.cn

    刘勇华:广东工业大学自动化学院副教授. 主要研究方向为非线性控制与智能控制. 本文通信作者. E-mail: yonghua.liu@outlook.com

    苏春翌:广东工业大学自动化学院教授. 主要研究方向为控制理论及其在机电系统中的应用. E-mail: chunyi.su@concordia.ca

Safe Control of Strict-feedback Systems Using Filtered Control Barrier Functions

Funds: Supported by National Natural Science Foundation of China (62173097, U2013601), GuangDong Basic and Applied Basic Research Foundation (2022A515011239), and the Local Innovative and Research Team Project of Guangdong Special Support Program (2019BT02X353)
More Information
    Author Bio:

    CHEN Zhong-Qiu Ph.D. candidate at the School of Automation, Guangdong University of Technology. Her research interest covers safety analysis and safety-critical control of nonlinear systems

    LIU Yong-Hua Associate professor at the School of Automation, Guangdong University of Technology. His research interest covers nonlinear and intelligent control. Corresponding author of this paper

    SU Chun-Yi Professor at the School of Automation, Guangdong University of Technology. His research interest covers control theory and its applications to mechanical systems

  • 摘要: 针对一类严格反馈系统的安全控制问题, 提出了一种基于滤波控制障碍函数(Filtered control barrier functions, FCBF)的优化控制方法. 首先引入一阶低通滤波器, 构建滤波控制障碍函数. 然后结合控制李雅普诺夫函数(Control Lyapunov functions, CLF)及离线优化技术, 提出了一种新颖的安全反推控制算法. 相比于现有文献, 本文所提控制方案通过运用滤波控制障碍函数, 有效克服了安全反推过程中的“计算膨胀”问题. 仿真结果验证了文中控制算法的有效性与正确性.
  • 图  1  不同滤波时间常数条件下系统的安全与跟踪性能

    Fig.  1  Safe and tracking performance of the system with various filter time constants

    图  2  基于FCBF与文献[26]控制方法的系统安全与跟踪性能

    Fig.  2  Safe and tracking performance of the system under the control schemes in FCBF and in reference [26]

    图  3  基于FCBF与文献[26]控制方法的系统输入$ u $

    Fig.  3  System input $ u $under the control schemes in FCBF and in reference [26]

    图  4  不同滤波时间常数条件下系统位置轨迹

    Fig.  4  Position trajectories of the system with various filter time constants

    图  5  不同滤波时间常数条件下输入信号$ u_1 $和$ u_2 $

    Fig.  5  Input signals $ u_1 $and $ u_2 $with various filter time constants

    图  6  基于FCBF与文献[26]控制方法的系统位置轨迹

    Fig.  6  Position trajectories of the system under the control schemes in FCBF and in reference [26]

    图  7  基于FCBF与文献[26]控制方法的输入信号$ u_1 $和$ u_2 $

    Fig.  7  Input signals $ u_1 $and $ u_2 $under the control schemes in FCBF and in reference [26]

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出版历程
  • 收稿日期:  2024-01-03
  • 录用日期:  2024-07-23
  • 网络出版日期:  2024-09-02

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