基于T-S 模糊模型的采样数据网络控制系统<em>H</em><sub>∞</sub> 输出跟踪控制

肖会芹; 何勇; 吴敏; 肖伸平

doi:10.16383/j.aas.2015.c140444

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

doi: 10.16383/j.aas.2015.c140444

1.
中南大学信息科学与工程学院长沙 410083;
2.
中国地质大学 (武汉) 自动化学院武汉 430074;
3.
湖南工业大学电气信息与工程学院株洲 412008

基金项目:

国家自然科学基金(61125301, 61210011, 61203136), 湖南省自然科学基金(12JJ4062) 资助

详细信息

作者简介:
肖会芹中南大学信息科学与工程学院博士研究生. 2000 年于湖南工业大学获自动化专业学士学位, 2006 年于中南大学获控制理论与控制工程学科硕士学位. 主要研究方向为时滞系统鲁棒控制和网络控制. E-mail: xiaohq610@126.com

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出版历程
- 收稿日期: 2014-06-24
- 修回日期: 2014-09-19

H_∞ Output Tracking Control for Sampled-data Networked Control Systems in T-S Fuzzy Model

1.
School of Information Science and Engineering, Central South University, Changsha 410083;
2.
School of Automation, China University of Geosciences, Wuhan 430074;
3.
College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412008

Funds:

Supported by National Natural Science Foundation of China (61125301, 61210011, 61203136), Hunan Provincial Natural Science Foundation of China (12JJ4062)

摘要

摘要: 研究具有采样数据的基于T-S (Takagi-Sugeno) 模糊模型网络控制系统H输出跟踪控制问题. 提出将采集器端数据采样周期、数据传输时滞和数据丢包转换为零阶保持器端数据更新周期, 在此基础上, 利用输入时滞法和PDC (Parallel distributed compensation) 技术, 建立网络环境下被控对象和参考模型合并的基于T-S 模糊模型的增广系统模型. 通过Lyapunov 方法, 并充分利用采样特性, 给出系统实现H输出跟踪的充分条件, 以及可靠模糊控制器的设计. 仿真结果表明所设计模糊控制器能够实现该类系统良好的跟踪.
- 采样数据网络控制系统 /
- T-S 模糊模型 /
- H∞输出跟踪控制 /
- 线性矩阵不等式
Abstract: This paper studies the problem of H output tracking control for sampled-data networked control systems in T-S (Takagi-Sugeno) fuzzy model. By using input-delay and parallel distributed compensation (PDC) techniques, an augment tracking model based on T-S fuzzy model is firstly established,in which the sampling period of the sampler, signal transmission delay and data packet dropouts are transformed to the refreshing interval of a zero-order holder. Furthermore, Lyapunov method is employed to derive several sucient criteria ensuring the prescribed H tracking performance. Meanwhile, a fuzzy controller design is also presented. Finally, a numerical example is given to illustrate that the designed fuzzy controller can realize good tracking.
- Sampled-data networked control systems /
- Takagi Sugeno (T-S) fuzzy model /
- H∞ output tracking control /
- linear matrix inequality (LMI)

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参考文献(25)

[1]	Dawson D M, Qu Z, Carroll J J. Tracking control of rigid-link electrically-driven robot manipulators. International Journal of Control, 1992, 56(5): 991-1006
[2]	Kim S H, Kim Y S, Song C. A robust adaptive nonlinear control approach to missile autopilot design. Control Engi- neering Practice, 2004, 12(2): 149-154
[3]	Liao F, Wang J L, Yang G H. Reliable robust fight tracking control: an LMI approach. IEEE Transactions on Control Systems Technology, 2002, 10(1): 76-89
[4]	Zhou Q, Shi P, Xu S Y, Li H Y. Adaptive output feedback control for nonlinear time-delay systems by fuzzy approxima- tion approach. IEEE Transactions on Fuzzy Systems, 2013,21(2): 301-313
[5]	Yao Yu, Zhang Bang-Cheng, Cai Yun, Zhou Zhi-Jie, Jiang Da-Wei, Gao Zhi. Improved strong track filter and its ap- plication to servo control system of 3PTT-2R institutions. Acta Automatica Sinica, 2014, 40(7): 1481-1492 (姚禹, 张邦成, 蔡赟, 周志杰, 姜大伟, 高智. 改进的强跟踪滤波算法及其在3PTT-2R 伺服系统中的应用. 自动化学报, 2014, 40(7):1481-1492)
[6]	Chen B, Liu X P, Ge S S, Lin C. Adaptive fuzzy control of a class of nonlinear systems by fuzzy approximation ap- proach. IEEE Transactions on Fuzzy Systems, 2012, 20(6):1012-1021
[7]	Li Xiang-Yang. Iterative learning control based on fnite time tracking diferentiator. Acta Automatica Sinica, 2014, 40(7):668 自动化学报41卷1366-1375 (李向阳. 基于有限时间跟踪微分器的迭代学习控制. 自动化学报,2014, 40(7): 1366-1375)
[8]	Tanaka K, Wang H O. Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach. New York: Wiley, 2001. 278-286
[9]	Lam H K, Li H Y, Christian D, Secco E L, Wurdemann H A, Kaspar A. Control design for internal type-2 fuzzy systems under imperfect premise matching. IEEE Transactions on Industrial Electronics, 2014, 61(2): 956-968
[10]	Wu Z G, Shi P, Su H Y, Chu J. Reliable control for discrete- time fuzzy systems with infinite-distributed delay. IEEE Transactions on Fuzzy Systems, 2012, 20(1): 22-31
[11]	Su X J, Shi P, Wu L G, Song Y D. A novel control design on discrete-time Takagi-Sugeno fuzzy systems with time- varying delays. IEEE Transactions on Fuzzy Systems, 2013,21(4): 655-671
[12]	Zhang Jian, Xu Hong-Bing, Zhang Hong-Bin. Observer- based sampled-data control for a class of continuous non- linear systems. Acta Automatica Sinica, 2010, 36(12):1780-1787 (张健, 徐红兵, 张洪斌. 基于观测器的一类连续非线性系统的采样控制. 自动化学报, 2010, 36(12): 1780-1787)
[13]	Hua C C, Wang Q G, Guan X P. Robust adaptive controller design for nonlinear time-delay systems via T-S fuzzy ap- proach. IEEE Transactions on Fuzzy Systems, 2009, 17(4):901-910
[14]	Lin C, Wang Q G, Lee T H. H1 output tracking control for nonlinear systems via T-S fuzzy model approach. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2006, 36(2): 450-457
[15]	Gao H J, Chen T W. Stabilization of nonlinear systems under variable sampling: a fuzzy control approach. IEEE Transac- tions on Fuzzy Systems, 2007, 15(5): 972-983
[16]	Wu Z G, Shi P, Su H, Chu J. Network-based robust passive control for fuzzy systems with randomly occurring uncer-tainties. IEEE Transactions on Fuzzy Systems, 2013, 21(5):966-971
[17]	You Ke-You, Xie Li-Hua. Survey of recent progress in networked control systems. Acta Automatica Sinica, 2013,39(2): 101-118 (游科友, 谢立华. 网络控制系统的最新研究综述. 自动化学报, 2013,39(2): 101-118)
[18]	Fridman E. A refined input delay approach to sampled-data control. Automatica, 2010, 46(2): 421-427
[19]	Zhang C K, Jiang L, He Y, Wu H, Wu M. Stability analysis for control systems with aperiodically sampled data using an augmented Lyapunov functional method. IET Control Theory and Applications, 2013, 7(9): 1219-1226
[20]	Xiao Hui-Qin, He Yong, Wu Min, Xiao Shen-Ping. Improved H1 tracking control for nonlinear networked control systems based on T-S fuzzy model. Control Theory Applications,2012, 29(1): 71-78 (肖会芹, 何勇, 吴敏, 肖伸平. 基于T-S 模糊模型非线性网络控制系统改进H1 跟踪控制. 控制理论与应用, 2012, 29(1): 71-78)
[21]	Jia X C, Zhang D W, Hao X H, Zheng N N. Fuzzy H1 tracking control for nonlinear networked control systems in T-S fuzzy model. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 2009, 39(4): 1073-1079
[22]	Chen Z S, He Y, Wu M. Robust fuzzy tracking control for nonlinear networked control systems with integral quadratic constraints. International Journal of Automation and Com- puting, 2010, 7(4): 492-499
[23]	Tanaka K, Yoshida H, Ohtake H, Wang H O. A sum-of-squares approach to modeling and control of nonlinear dynamical systems with polynomial fuzzy systems. IEEE Transactions on Fuzzy Systems, 2009, 17(4): 911-922
[24]	Zhao X D, Zhang L X, Shi P, Karimi H R. Novel stability criteria for T-S fuzzy systems. IEEE Transactions on Fuzzy Systems, 2014, 22(2): 313-323
[25]	Tanaka K, Ikeda T, Wang H O. A united approach to controlling chaos via an LMI-based fuzzy control system design. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 1998, 45(10): 1021-1040

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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

doi: 10.16383/j.aas.2015.c140444

作者简介:
肖会芹中南大学信息科学与工程学院博士研究生. 2000 年于湖南工业大学获自动化专业学士学位, 2006 年于中南大学获控制理论与控制工程学科硕士学位. 主要研究方向为时滞系统鲁棒控制和网络控制. E-mail: xiaohq610@126.com

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H_∞ Output Tracking Control for Sampled-data Networked Control Systems in T-S Fuzzy Model

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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

doi: 10.16383/j.aas.2015.c140444

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出版历程

H∞ Output Tracking Control for Sampled-data Networked Control Systems in T-S Fuzzy Model

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出版历程

目录

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

H_∞ Output Tracking Control for Sampled-data Networked Control Systems in T-S Fuzzy Model