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基于全驱系统方法的高阶严反馈系统时变输出约束控制

蔡光斌 肖永强 胡昌华 杨小冈 凡永华

蔡光斌, 肖永强, 胡昌华, 杨小冈, 凡永华. 基于全驱系统方法的高阶严反馈系统时变输出约束控制. 自动化学报, 2024, 50(2): 372−385 doi: 10.16383/j.aas.c230441
引用本文: 蔡光斌, 肖永强, 胡昌华, 杨小冈, 凡永华. 基于全驱系统方法的高阶严反馈系统时变输出约束控制. 自动化学报, 2024, 50(2): 372−385 doi: 10.16383/j.aas.c230441
Cai Guang-Bin, Xiao Yong-Qiang, Hu Chang-Hua, Yang Xiao-Gang, Fan Yong-Hua. Time-varying output constraint control of high-order strict-feedback systems based on fully actuated system approach. Acta Automatica Sinica, 2024, 50(2): 372−385 doi: 10.16383/j.aas.c230441
Citation: Cai Guang-Bin, Xiao Yong-Qiang, Hu Chang-Hua, Yang Xiao-Gang, Fan Yong-Hua. Time-varying output constraint control of high-order strict-feedback systems based on fully actuated system approach. Acta Automatica Sinica, 2024, 50(2): 372−385 doi: 10.16383/j.aas.c230441

基于全驱系统方法的高阶严反馈系统时变输出约束控制

doi: 10.16383/j.aas.c230441
基金项目: 国家自然科学基金(61773387, 62073096), 国家自然科学基金委基础科学中心项目(62188101)资助
详细信息
    作者简介:

    蔡光斌:博士, 火箭军工程大学副教授. 主要研究方向为新型飞行器制导与控制, 智能控制理论及应用. E-mail: cgb0712@163.com

    肖永强:火箭军工程大学博士研究生. 主要研究方向为全驱系统方法, 非线性控制理论及其在飞行器控制中的应用. 本文通信作者. E-mail: xyqiang163@163.com

    胡昌华:博士, 火箭军工程大学教授. 主要研究方向为故障诊断与预测, 容错控制, 先进控制理论及应用. E-mail: hch66603@163.com

    杨小冈:博士, 火箭军工程大学教授. 主要研究方向为飞行器精确制导与控制技术. E-mail: doctoryxg@163.com

    凡永华:博士, 西北工业大学航天学院研究员. 主要研究方向为飞行器制导控制系统设计及仿真. E-mail: fanyonghua@nwpu.edu.cn

Time-varying Output Constraint Control of High-order Strict-feedback Systems Based on Fully Actuated System Approach

Funds: Supported by National Natural Science Foundation of China (61773387, 62073096) and Science Center Program of National Natural Science Foundation of China (62188101)
More Information
    Author Bio:

    CAI Guang-Bin Ph.D., associate professor at Rocket Force University of Engineering. His research interest covers new aircraft guidance and control, and intelligent control theory and application

    XIAO Yong-Qiang Ph.D. candidate at Rocket Force University of Engineering. His research interest covers fully actuated system approach, nonlinear control theory, and its application in aircraft control. Corresponding author of this paper

    HU Chang-Hua Ph.D., professor at Rocket Force University of Engineering. His research interest covers fault diagnosis and prediction, fault tolerant control, and advanced control theory and application

    YANG Xiao-Gang Ph.D., professor at Rocket Force University of Engineering. His research interest covers aircraft precision guidance and control technology

    FAN Yong-Hua Ph.D., research fellow at the School of Astronautics, Northwestern Polytechnic University. His research interest covers design and simulation of aircraft guidance and control system

  • 摘要: 针对输出受不对称时变约束的不确定高阶严反馈系统, 提出一种基于全驱系统方法的高阶自适应动态面输出约束控制方法. 所研究的高阶严反馈系统, 每个子系统都是高阶形式, 通过非线性转换函数将原输出约束系统转换为新的无约束系统, 从而将原系统输出约束问题转化为新系统输出有界的问题. 进一步结合全驱系统方法和自适应动态面控制, 直接将每个高阶子系统作为一个整体进行控制器设计, 而不需要将其转化为一阶系统形式, 有效简化了设计步骤; 同时通过引入一系列低通滤波器来获得虚拟控制律的高阶导数, 以代替复杂的微分运算. 基于Lyapunov稳定性理论证明闭环系统所有信号是一致最终有界的, 系统输出在满足约束的条件下能有效跟踪期望的参考信号, 且可通过调整参数使得系统跟踪误差收敛到零附近的足够小的邻域内. 最后, 通过对柔性关节机械臂系统进行仿真, 验证了所提出控制方法的有效性.
  • 图  1  情况1下的系统输出跟踪结果

    Fig.  1  System output tracking results in Case 1

    图  2  情况2下的系统输出跟踪结果

    Fig.  2  System output tracking results in Case 2

    图  3  系统输出跟踪结果(情况1)

    Fig.  3  System output tracking results (Case 1)

    图  4  系统跟踪误差(情况1)

    Fig.  4  System tracking errors (Case 1)

    图  5  参数估计${\hat{\theta} _1}(h)$, ${\hat{\theta} _1}(f1)$, ${\hat{\theta} _1}(f2)$(情况1)

    Fig.  5  Parameter estimation ${\hat{\theta} _1}(h)$, ${\hat{\theta} _1}(f1)$, and ${\hat{\theta} _1}(f2)$(Case 1)

    图  6  参数估计${\hat{\theta} _2}(h)$, ${\hat{\theta} _2}(f1)$, ${\hat{\theta} _2}(f2)$(情况1)

    Fig.  6  Parameter estimation ${\hat{\theta} _2}(h)$, ${\hat{\theta} _2}(f1)$, and ${\hat{\theta} _2}(f2)$(Case 1)

    图  7  系统控制输入(情况1)

    Fig.  7  System control inputs (Case 1)

    图  8  系统输出跟踪结果(情况2)

    Fig.  8  System output tracking results (Case 2)

    图  9  系统跟踪误差(情况2)

    Fig.  9  System tracking errors (Case 2)

    图  10  参数估计${\hat{\theta} _1}(h)$, ${\hat{\theta} _1}(f1)$, ${\hat{\theta} _1}(f2)$(情况2)

    Fig.  10  Parameter estimation ${\hat{\theta} _1}(h)$, ${\hat{\theta} _1}(f1)$, and ${\hat{\theta} _1}(f2)$(Case 2)

    图  11  参数估计${\hat{\theta} _2}(h)$, ${\hat{\theta} _2}(f1)$, ${\hat{\theta} _2}(f2)$(情况2)

    Fig.  11  Parameter estimation ${\hat{\theta} _2}(h)$, ${\hat{\theta} _2}(f1)$, and ${\hat{\theta} _2}(f2)$(Case 2)

    图  12  系统控制输入(情况2)

    Fig.  12  System control inputs (Case 2)

    表  1  三种算法运算时间对比(s)

    Table  1  Comparison of operation time of three algorithms (s)

    本文方法一阶BLF方法一阶NM方法
    情况144.38038358.87963149.213382
    情况235.17354547.96532441.693068
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-07-19
  • 录用日期:  2023-10-05
  • 网络出版日期:  2024-01-17
  • 刊出日期:  2024-02-26

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