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基于T-S模糊模型的采样系统鲁棒耗散控制

练红海 肖伸平 罗毅平 周笔锋

练红海, 肖伸平, 罗毅平, 周笔锋. 基于T-S模糊模型的采样系统鲁棒耗散控制. 自动化学报, 2022, 48(11): 2852−2862 doi: 10.16383/j.aas.c190309
引用本文: 练红海, 肖伸平, 罗毅平, 周笔锋. 基于T-S模糊模型的采样系统鲁棒耗散控制. 自动化学报, 2022, 48(11): 2852−2862 doi: 10.16383/j.aas.c190309
Lian Hong-Hai, Xiao Shen-Ping, Luo Yi-Ping, Zhou Bi-Feng. Robust dissipative control for sampled-data system based on T-S fuzzy model. Acta Automatica Sinica, 2022, 48(11): 2852−2862 doi: 10.16383/j.aas.c190309
Citation: Lian Hong-Hai, Xiao Shen-Ping, Luo Yi-Ping, Zhou Bi-Feng. Robust dissipative control for sampled-data system based on T-S fuzzy model. Acta Automatica Sinica, 2022, 48(11): 2852−2862 doi: 10.16383/j.aas.c190309

基于T-S模糊模型的采样系统鲁棒耗散控制

doi: 10.16383/j.aas.c190309
基金项目: 国家自然科学基金(61672225, 61741308), 湖南省自然科学基金(2018JJ2096, 2018JJ4075, 2020JJ7023), 湖南电气职业技术学院自然科学基金重点项目(2019ZK002)资助
详细信息
    作者简介:

    练红海:湖南电气职业技术学院特聘教授. 2017年获得湖南工业大学控制理论与控制工程专业硕士学位. 主要研究方向为时滞控制系统, 采样控制系统, 电力系统稳定与控制. E-mail: lianhh402@163.com

    肖伸平:湖南工业大学教授. 2008年获得中南大学控制理论与控制工程专业博士学位. 主要研究方向为鲁棒控制, 智能控制与过程控制. 本文通信作者. E-mail: xsph159@163.com

    罗毅平:湖南工程学院教授. 2006年获得华南理工大学博士学位. 主要研究方向为复杂网络系统, 分布参数系统. E-mail: lyp8688@sohu.com

    周笔锋:湖南电气职业技术学院讲师. 2015年获得湖南工程学院硕士学位. 主要研究方向为复杂网络系统, 分布参数系统. E-mail: zhoubifeng99@163.com

Robust Dissipative Control for Sampled-data System Based on T-S Fuzzy Model

Funds: Supported by National Natural Science Foundation of China (61672225, 61741308), Natural Sciences Foundation of Hunan Province (2018JJ2096, 2018JJ4075, 2020JJ7023), and Natural Sciences Foundation of Hunan Electrical College of Technology (2019ZK002)
More Information
    Author Bio:

    LIAN Hong-Hai Special-term professor at Hunan Electrical College of Technology. He received his master degree from Hunan University of Technology in 2017. His research interest covers time-delay systems, sampled-data systems, and robust control

    XIAO Shen-Ping Professor at Hunan University of Technology. He received his Ph.D. degree from Central South University in 2008. His research interest covers robust control, intelligent control, and process control. Corresponding author of this paper

    LUO Yi-Ping Professor at Hunan Institute of Engineering. He received his Ph.D. degree from South China University of Technology. His research interest covers complex networks and distributed parameter systems

    ZHOU Bi-Feng Lecturer at Hunan Electrical College of Technology. He received his master degree form Hunan Institute of Engineering in 2015. His research interest covers complex networks and distributed parameter systems

  • 摘要: 研究基于T-S (Takagi-Sugeno)模糊模型的采样控制系统鲁棒耗散控制问题. 利用2阶B-L (Bessel-Legendre)不等式和整个采样间隔 $\left[ {{t_k},{t_{k + 1}}} \right)$的特征信息, 提出一个基于B-L不等式的双边时间相关不连续L-K (Lyapunov-Krasovskii)泛函. 使用提出的L-K泛函和改进的自由矩阵不等式, 建立了确保系统严格($\mathcal{Q}$, $\mathcal{S}$, $\mathcal{R}$)-$\gamma$-耗散的充分条件. 基于所得耗散条件, 给出了T-S模糊采样控制器的设计方法, 并用于处理卡车拖车的控制问题. 仿真结果表明所提出的控制器设计方法非常有效.
  • 图  1  卡车拖车模型及其坐标系统

    Fig.  1  Truck trailer model and its coordinate system

    图  2  变周期采样$h_k \in (0,0.26]$的系统状态响应

    Fig.  2  State response of system in the case of variable sampling with $h_k \in (0,0.26]$

    图  3  变周期采样$h_k \in (0,0.26]$ 的系统控制输入

    Fig.  3  Control input of system (38) in the case of variable sampling with $h_k \in (0,0.26]$

    图  4  定周期采样$h_2 = 0.32$的系统状态响应

    Fig.  4  State response of system in the case of constant sampling with $h_2 = 0.32$

    图  5  定周期采样$h_2 = 0.32$的系统控制输入

    Fig.  5  Control input of system in the case of constant sampling with $h_2 = 0.32$

    表  1  对不同$ h_2 $$\gamma_{\max}$

    Table  1  $\gamma_{\max}$ for different $ h_2 $

    $h_2$0.050.100.150.200.250.35
    文献 [30]0.99710.96710.93110.88420.8193
    推论 11.06361.04631.02640.99780.95540.7484
    定理 21.06431.04721.02720.99940.95590.7564
    下载: 导出CSV

    表  2  对不同$ h_1 $$\gamma_{\max}$

    Table  2  $\gamma_{\max}$ for different $ h_1 $

    $h_1$0.100.150.200.250.30.35
    定理 20.81080.83500.85460.87160.88540.9026
    下载: 导出CSV

    表  3  对不同$ h_1 = h_2 $$\gamma_{\max}$

    Table  3  $\gamma_{\max}$ for different $ h_1 = h_2 $

    $h_1=h_2$0.050.100.150.200.250.35
    定理 21.06791.05721.04471.02831.00720.9026
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-04-19
  • 录用日期:  2019-09-09
  • 网络出版日期:  2022-08-04
  • 刊出日期:  2022-11-22

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