Stabilization of nonlinear safety-critical systems by relaxed converse Lyapunov-barrier approach and its applications in robotic systems

被引:0
|
作者
Li, Haoqi [1 ,2 ]
Hu, Jiangping [1 ,2 ]
Hu, Xiaoming [3 ]
Ghosh, Bijoy K. [4 ]
机构
[1] School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu,611731, China
[2] Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou,313000, China
[3] Optimization and Systems Theory, Royal Institute of Technology, Stockholm,SE-100 44, Sweden
[4] Department of Mathematics and Statistics, Texas Tech University, Lubbock,TX,79409-1042, United States
来源
Autonomous Intelligent Systems | 2024年 / 4卷 / 01期
关键词
Affine transforms - Control system stability - Lyapunov methods - Nonlinear systems - Stabilization;
D O I
10.1007/s43684-024-00081-x
中图分类号
学科分类号
摘要
Combining safety objectives with stability objectives is crucial for safety-critical systems. Existing studies generally unified these two objectives by constructing Lyapunov-type barrier functions. However, insufficient analysis of key set relationships within the system may render the proposed safety and stability conditions conservative, and these studies also did not provide how to use such conditions to design safety-stability control strategies. This paper proposed a feasible and constructive design to achieve stabilization of safety-critical systems by a relaxed converse Lyapunov-barrier approach. By analyzing the relationships between a series of sets associated with the safety-critical system, the stability and safety conditions can be appropriately relaxed. Then, with the help of relaxed converse control Lyapunov-barrier functions (RCCLBFs), a theoretical result was obtained for the stability of affine nonlinear systems with safety constraints. Subsequently, a constructive method was developed for a second-order strict-feedback system to transform the process of solving RCCLBFs into a Lyapunov-like stabilization problem. Finally, the proposed safety-stability control method is exerted on a robotic system and demonstrated by simulations. © The Author(s) 2024.
引用
收藏
相关论文
共 50 条
  • [1] Safety Analysis and Safety-critical Control of Nonlinear Systems: Barrier Function Approach
    Chen J.
    Lyu Z.-L.
    Huang X.-Y.
    Hong Y.-G.
    Zidonghua Xuebao/Acta Automatica Sinica, 2023, 49 (03): : 567 - 579
  • [2] Safety-Critical Kinematic Control of Robotic Systems
    Singletary, Andrew
    Kolathaya, Shishir
    Ames, Aaron D.
    IEEE CONTROL SYSTEMS LETTERS, 2022, 6 : 139 - 144
  • [3] Safety-Critical Kinematic Control of Robotic Systems
    Singletary, Andrew
    Kolathaya, Shishir
    Ames, Aaron D.
    2021 AMERICAN CONTROL CONFERENCE (ACC), 2021, : 14 - 19
  • [4] Robust adaptive control Lyapunov-barrier function for non-collocated control and safety of underactuated robotic systems
    Azimi, Vahid
    Hutchinson, Seth
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2022, 32 (13) : 7363 - 7390
  • [5] A Barrier-Based Scenario Approach to Verifying Safety-Critical Systems
    Akella, Prithvi
    Ames, Aaron D.
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (04) : 11062 - 11069
  • [6] Concurrent Learning Control Lyapunov and Barrier Functions for Uncertain Nonlinear Safety-Critical Systems With High Relative Degree Constraints
    Wang, Liqi
    Dong, Jiuxiang
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, 21 (04) : 7170 - 7179
  • [7] Safety-critical control for robotic systems with uncertain model via control barrier function
    Zhang, Sihua
    Zhai, Di-Hua
    Xiong, Yuhan
    Lin, Juncheng
    Xia, Yuanqing
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2023, 33 (06) : 3661 - 3676
  • [8] Control Lyapunov-Barrier function-based model predictive control of nonlinear systems
    Wu, Zhe
    Albalawi, Fahad
    Zhang, Zhihao
    Zhang, Junfeng
    Durand, Helen
    Christofides, Panagiotis D.
    AUTOMATICA, 2019, 109
  • [9] Adaptive safety-critical control for a class of nonlinear systems with parametric uncertainties: A control barrier function approach
    Wang, Yujie
    Xu, Xiangru
    SYSTEMS & CONTROL LETTERS, 2024, 188
  • [10] Control Lyapunov-Barrier Function-Based Model Predictive Control of Nonlinear Systems
    Wu, Zhe
    Albalawi, Fahad
    Zhang, Zhihao
    Zhang, Junfeng
    Durand, Helen
    Christofides, Panagiotis D.
    2018 ANNUAL AMERICAN CONTROL CONFERENCE (ACC), 2018, : 5920 - 5926