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具有软硬输出约束的不确定非线性系统漏斗控制: 一种直接修正方法

左凰 陶杰 林明 刘勇华 苏春翌

左凰, 陶杰, 林明, 刘勇华, 苏春翌. 具有软硬输出约束的不确定非线性系统漏斗控制: 一种直接修正方法. 自动化学报, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c260016
引用本文: 左凰, 陶杰, 林明, 刘勇华, 苏春翌. 具有软硬输出约束的不确定非线性系统漏斗控制: 一种直接修正方法. 自动化学报, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c260016
Zuo Huang, Tao Jie, Lin Ming, Liu Yong-Hua, Su Chun-Yi. Funnel control for uncertain nonlinear systems under soft and hard output constraints: a direct modification approach. Acta Automatica Sinica, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c260016
Citation: Zuo Huang, Tao Jie, Lin Ming, Liu Yong-Hua, Su Chun-Yi. Funnel control for uncertain nonlinear systems under soft and hard output constraints: a direct modification approach. Acta Automatica Sinica, xxxx, xx(x): x−xx doi: 10.16383/j.aas.c260016

具有软硬输出约束的不确定非线性系统漏斗控制: 一种直接修正方法

doi: 10.16383/j.aas.c260016 cstr: 32138.14.j.aas.c260016
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:

    左凰: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控制与约束控制. E-mail: pengpqcw32309@163.com

    陶杰:广东工业大学自动化学院教授. 主要研究方向为基于事件的控制与无人机系统. E-mail: taojiedyx@163.com

    林明:广东工业大学自动化学院教授. 主要研究方向为高速光通信、网络化控制系统及5G应用. E-mail: linming@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

  • 中图分类号: Y

Funnel Control for Uncertain Nonlinear Systems Under Soft and Hard Output Constraints: A Direct Modification Approach

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:

    ZUO Huang Ph.D. candidate at the School of Automation, Guangdong University of Technology. His research interests include nonlinear control and constrained control

    TAO Jie Professor at the School of Automation, Guangdong University of Technology. His research interests include event-based control and unmanned aerial vehicle systems

    LIN Ming Professor at the School of Automation, Guangdong University of Technology. His research interests include high-speed optical communication, networked control systems, and 5G applications

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

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

  • 摘要: 本文研究了一类同时存在软、硬输出约束的不确定非线性系统跟踪控制问题. 其中, 安全相关的输出约束被建模为不可违背的硬约束, 而期望的跟踪性能则通过可调节的软约束加以刻画. 针对软、硬约束可能发生冲突的情形, 引入一种光滑过渡函数, 并基于此构造凸组合算子对软约束边界进行直接修正, 从而保证其与硬约束的兼容性. 在此基础上, 将硬约束与修正后的软约束进行统一整合, 构造具有光滑边界的约束结构. 基于该约束结构并结合漏斗控制技术, 提出一种低复杂度鲁棒控制算法, 确保系统同时满足硬约束与修正后的软约束. 与现有基于辅助动态系统的软约束间接调整方法不同, 所提策略无需引入额外动态系统, 从而得到结构简洁、易于实现的静态控制器. 此外, 在软、硬约束冲突发生时, 该方法能够将软约束的违背量严格限制在硬约束所必需的最小违背量之上的预设容差范围内, 且在有限时间内实现约束解耦, 优先确保硬约束的严格满足. 仿真结果验证了该方法的有效性.
  • 图  1  可行域内的输出轨迹y

    Fig.  1  Output trajectory y within the feasible region

    图  2  修正后的软约束边界$\overline{p}$和$\underline{p}$

    Fig.  2  Modified soft constraint boundaries $\overline{p}$ and $\underline{p}$

    图  3  整合的光滑约束边界$\overline{\rho}$和$\underline{\rho}$

    Fig.  3  Consolidated smooth constraint boundaries $\overline{\rho}$ and $\underline{\rho}$

    图  4  控制输入$u$

    Fig.  4  Control input $u$

    图  5  凸组合系数$\mu_1$和$\mu_2$

    Fig.  5  Convex combination coefficients $\mu_1$ and $\mu_2$

    图  6  不同容差参数$\delta$下软约束违背量对比

    Fig.  6  Comparison of soft-constraint violation under different tolerance parameters $\delta$

    表  1  时间区间$ [0,\;12] $上的性能指标对比

    Table  1  Comparison of performance indices on the time interval $ [0,\;12] $

    $ \|e\|_{L^2} $ $ \alpha $ $ \beta $
    本文方法 0.40 97.31% 0.0095
    文献[46] 0.71 78.03% 0.1471
    下载: 导出CSV

    表  2  不同仿真时长下的计算时间对比 (s)

    Table  2  Comparison of computational time under different simulation durations (s)

    $ T=12 $ $ T=50 $ $ T=100 $
    本文方法 1.00 3.95 7.60
    文献[46] 1.08 4.55 10.19
    下载: 导出CSV
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  • 收稿日期:  2026-01-07
  • 录用日期:  2026-04-01
  • 网络出版日期:  2026-05-18

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