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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
  • [1] Takagi T, Sugeno M. Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man, and Cybernetics, 1985, 15(1): 116−132
    [2] Garcia-Nunes P I, Souza R M, Sliva A E. Mental models analysis and comparison based on fuzzy rules: A case study of the protests of June and July 2013 in Brazil. IEEE Transactions on Systems, Man, and Cybernetics, 2017, 47(8): 2021−2033 doi: 10.1109/TSMC.2016.2598767
    [3] Li H, Jing X, Lam H K, Shi P. Fuzzy sampled-data control for uncertain vehicle suspension systems. IEEE Transactions on Cybernetics, 2014, 44(7): 1111−1126 doi: 10.1109/TCYB.2013.2279534
    [4] Wu Z G, Dong S, Su H, Huang T. Fuzzy-model-based nonfragile guaranteed cost control of nonlinear markov jump systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(8): 2388−2397 doi: 10.1109/TSMC.2017.2675943
    [5] 肖会芹, 何勇, 吴敏, 肖伸平. 基于T-S模糊模型的采样数据网络控制系统H输出跟踪控制. 自动化学报, 2015, 41(3): 661−668

    Xiao Hui-Qin, He Yong, Wu Min, Xiao Shen-Ping. H output tracking for sampled-data networked control systems in T-S Fuzzy model. Acta Automatica Sinica, 2015, 41(3): 661−668
    [6] Xiao H Q, He Y, Wu M, Xiao S P. New results on H tracking control based on the T-S fuzzy model for sampleddata networked control system. IEEE Transactions on Fuzzy Systems, 2015, 23(6): 2439−2448 doi: 10.1109/TFUZZ.2015.2410790
    [7] Zhang D, Cai W, Xie L, Wang Q G. Nonfragile distributed filtering for T-S fuzzy systems in sensor networks. IEEE Transactions on Fuzzy Systems, 2015, 23(5): 1883−1890 doi: 10.1109/TFUZZ.2014.2367101
    [8] Su X, Shi P, Wu L, Basin M V. Reliable filtering with strict dissipativity for T-s fuzzy time-delay systems. IEEE Transactions on Cybernetics, 2014, 44(12): 2470−2483 doi: 10.1109/TCYB.2014.2308983
    [9] Li H, Gao Y, Wu L, Lam H K. Fault detection for T-S fuzzy time-delay systems: delta operator and input-output methods. IEEE Transactions on Cybernetics, 2015, 45(2): 229−241 doi: 10.1109/TCYB.2014.2323994
    [10] Fujioka H. A Discrete-time approach to stability analysis of systems with aperiodic sample-and-hold devices. IEEE Transactions on Automatica Control, 2009, 54(10): 2440−2445 doi: 10.1109/TAC.2009.2029304
    [11] Jiang X, Yin Z, Wu J. Stability analysis of linear systems under time-varying samplings by a non-standard discretization method. Eelectonics, 2018, 7(11): 1−11
    [12] Briatab C, Seuret A. A looped-functional approach for robust stability analysis of linear impulsive systems. Systems & Control Letters, 2012, 61(10): 980−998
    [13] Fridman E, Seuret A, Richard J P. Robust sampled-data stabilization of linear systems: an input delay approach. Automatica, 2004, 40(8): 378−385
    [14] Seuret A, Couaisbaut F. Wirtinger-based integral inequality: application to time-delay systems. Automatica, 2013, 49: 2860−2866 doi: 10.1016/j.automatica.2013.05.030
    [15] Seuret A, Briat C. Stability analysis of uncertain sampleddata systems with incremental delay using loopedfunctionals. Automatica, 2015, 55: 274−278 doi: 10.1016/j.automatica.2015.03.015
    [16] Lian H H, Xiao S P, Wang Z, Zhang X F, Xiao H Q. Further results on sampled-data synchronization control for chaotic neural networks with actuator saturation. Nerocomputing, 2019, 346: 30−37 doi: 10.1016/j.neucom.2018.08.090
    [17] Lee T H, Ju H P. Stability analysis of sampled-data systems via free-matrix-based time-dependent discontinuous Lyapunov approach . IEEE Transactions on Automatic Control, 2017, 48(1): 3653−3657
    [18] Zeng H B, Teo K. L, He Y. A new looped-functional for stability analysis of sampled-data systems. Automatica, 2017, 82: 328−331 doi: 10.1016/j.automatica.2017.04.051
    [19] Lee S M, Kwon O M, Lee S H. Improved stability criteria for sampled-data systems using modified free weighting matrix. Journal of the Franklin Institute, 2019, 356: 2198−2211 doi: 10.1016/j.jfranklin.2018.12.016
    [20] Zeng H B, Teo K L, He Y, Wang W. Sampled-data stabilization of chaotic systems based on a T-S fuzzy model. Information Sciences, 2019, 483: 262−272 doi: 10.1016/j.ins.2019.01.046
    [21] Zhang R, Zeng D, Park J H, Liu Y, Zhong S. A new approach to stabilization of chaotic systems with nonfragile fuzzy proportional retarded sampled-data control. IEEE Transactions on Cyberneticss, 2019, 49(9): 3218−3229 doi: 10.1109/TCYB.2018.2831782
    [22] Lee T H, Park J H. New methods of fuzzy sampled-data control for stabilization of chaotic systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018, 48(12): 2026−2034 doi: 10.1109/TSMC.2017.2690803
    [23] Xiao S P, Lian H H, Teo K L, Zeng H B, ZHANG X H. A new Lyapunov functional approach to sampled-data synchronization control for delayed neural networks. Journal of the Franklin Institute, 2018, 355: 8857−8873 doi: 10.1016/j.jfranklin.2018.09.022
    [24] B. Zhang, W. X. Zheng, S. Xu. Filtering of Markovian jump delay systems based on a new performance index. IEEE Transactions on Circuits and Systems I: Regular Paper, 2013, 60(3): 1250−1263
    [25] Shi P, Su X, Li F. Dissipativity-based filtering for fuzzy switched systems with stochastic perturbation. IEEE Transactions on Automatic Control, 2016, 61(6): 694−1699
    [26] 肖伸平, 练红海, 陈刚, 冯磊. 时变时滞神经网络的时滞相关鲁棒稳定性和耗散性分析. 控制与决策, 2017, 32(6): 1084−1090

    Xiao Shen-Ping, Lian Hong-Hai, Chen Gang, Feng Lei. Delay-dependent robust stability and dissipativity analysis of neural networks with time-varying delays. Control and Decision, 2017, 32(6): 1084−1090
    [27] Ma Y, Jia X, Liu D. Finite-time dissipative control for singular discrete-time Markovian jump systems with actuator saturation and partly unknown transition rates. Applied Mathematical Modelling, 2018, 53: 49−70 doi: 10.1016/j.apm.2017.07.035
    [28] Tao J, Lu R, Shi P, Su H, Wu Z G. Dissipativity-based reliable control for fuzzy Markov jump systems with actuator faults. IEEE Transactions on Cybernetics, 2017, 47(9): 2377−2388 doi: 10.1109/TCYB.2016.2584087
    [29] Wang S, Ji W, Pang J, Jian Y. Dissipativity-based sampleddata reliable control design for T-S fuzzy system using limited Bessel-Legendre inequaliity. IEEE Access, 2018, 6: 73405−73415 doi: 10.1109/ACCESS.2018.2882125
    [30] Wu Z G, Shi P, Su H, Lu R. Dissipativity-based sampleddata fuzzy control design and its application to truck-trailer system. IEEE Transactions on Fuzzy Systems, 2015, 23(5): 1669−1679 doi: 10.1109/TFUZZ.2014.2374192
    [31] Zeng H B, Teo K L, He Y, Wang W. Sampled-data-Based dissipative control of T-S fuzzy systems. Applied Mathematical Modelling, 2019, 65: 415−427 doi: 10.1016/j.apm.2018.08.012
    [32] Hill D, Moylan P. The stability of nonlinear dissipative system. IEEE Transactions on Automatic Control, 1976, 21: 708−711 doi: 10.1109/TAC.1976.1101352
    [33] Zhang X M, Han Q L, Zeng Z G. Hierarchical type stability criteria for delayed neural networks via canonical sessellegendre inequalities. IEEE Transactions on Cybernetics, 2018, 48(5): 1660−1671 doi: 10.1109/TCYB.2017.2776283
    [34] Seuret A, Gouaisbaut F. Stability of linear systems with time-varying delays using Bessel-Legendre inequalities. IEEE Transactions on Automatic Control, 2018, 63(1): 225−232 doi: 10.1109/TAC.2017.2730485
    [35] Zeng H B, He Y, Wu M. New results on stability analysis for systems with discrete distributed delay. Automatica, 2015, 60: 189−192 doi: 10.1016/j.automatica.2015.07.017
    [36] Lian Z, He Y, Zhang C K, Wu M. Stability and stabilization of T-S fuzzy systems with time-varying delays via delay-product-type functional method. IEEE Transactions on Cybernetics, 2020, 50(6): 2580−2589
    [37] 唐晓铭, 邓梨, 虞继敏, 屈洪春. 基于区间二型T-S模糊模型的网络控制系统的输出反馈预测控制. 自动化学报, 2019, 45(3): 604−616

    Tang Xiao-Ming, Deng Li, Yu Ji-Min, Qu Hong-Chun. Output feedback model predictive control for interval Type-2 T-S Fuzzy Networked Control Systems. Acta Automatica Sinica, 2019, 45(3): 604−616
    [38] 张必山, 马忠军, 杨美香. 既含有一般多个随机延迟以及多个测量丢失和随机控制丢失的鲁棒H模糊输出反馈控制. 自动化学报, 2017, 43(9): 1656−1664

    Zhang Bi-Shan, Ma Zhong-Jun, Yang Mei-Xiang. Robust H fuzzy output-feedback control with both general multiple probabilistic delays and multiple missing measurements and random missing control. Acta Automatica Sinica, 2017, 43(9): 1656−1664
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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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