[1] Chu Hongyan, Fei Shumin, Chen Haixia, et al. T-S-fuzzy-model-based quantized controlfor nonlinear networked control systems [J]. Journal of Southeast University (English Edition), 2010, 26 (1): 137-141. [doi:10.3969/j.issn.1003-7985.2010.01028]

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T-S-fuzzy-model-based quantized controlfor nonlinear networked control systems()

基于T-S模糊模型的非线性网络控制系统的量化控制

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

26

Issue:

2010 1

Page:

137-141

Research Field:

Automation

Publishing date:

2010-03-30

Info

Title:

T-S-fuzzy-model-based quantized controlfor nonlinear networked control systems

基于T-S模糊模型的非线性网络控制系统的量化控制

Author(s):

Chu Hongyan^{1, 2}, Fei Shumin¹, Chen Haixia³, Zhai Junyong¹

¹ School of Automation, Southeast University, Nanjing 210096, China
² School of Electrical and Automatic Engineering, Nanjing Normal University, Nanjing 210042, China
³ School of Electrical and Automatic Engineerin

褚红燕^{1, 2}, 费树岷¹, 陈海霞³, 翟军勇¹

¹东南大学自动化学院, 南京 210096; ²南京师范大学电气与自动化工程学院, 南京 210042; ³三江学院电气与自动化工程学院, 南京 210008

Keywords:

T-S fuzzy model;  linear matrix inequalities(LMIs);  quantizers

T-S模糊模型;  线性矩阵不等式;  量化器

PACS:

TP273

DOI:

10.3969/j.issn.1003-7985.2010.01028

Abstract:

In order to overcome data-quantization, networked-induced delay, network packet dropouts and wrong sequences in the nonlinear networked control system, a novel nonlinear networked control system model is built by the T-S fuzzy method. Two time-varying quantizers are added in the model. The key analysis steps in the method are to construct an improved interval-delay-dependent Lyapunov functional and to introduce the free-weighting matrix. By making use of the parallel distributed compensation technology and the convexity of the matrix function, the improved criteria of the stabilization and stability are obtained. Simulation experiments show that the parameters of the controllers and quantizers satisfying a certain performance can be obtained by solving a set of LMIs. The application of the nonlinear mass-spring system is provided to show that the proposed method is effective.

为了克服数据量化、网络诱导时滞、网络丢包及错序对非线性网络控制系统造成的影响, 采用T-S模糊建模方法建立了一个新的非线性网络控制系统模型, 并在系统模型中加入2个时变量化器. 主要分析方法在于通过构造一个改进的区间时滞依赖的李雅普诺夫函数, 并引入自由权矩阵.利用并行分布式补偿技术和矩阵函数的凸性, 得出了改进系统的稳定和镇定的条件. 仿真实验表明, 通过求解一组线性矩阵不等式, 可得保证系统渐近稳定并满足一定性能的控制器参数和量化器参数. 在具有非线性的弹簧系统中的应用验证了所提方法的有效性.

References:

[1] Zhang W, Branicky M S. Stability of networked control systems [J]. IEEE Control Systems Magazine, 2001, 21(1): 84-99.
[2] Walsh G, Ye H. Stability analysis of networked control systems [J]. IEEE Trans Control Systems Technology, 2002, 10(3): 438-446.
[3] Yue D, Han Q L. State feedback controller design of networked control systems [J]. IEEE Trans Circuits and Systems Ⅱ, 2004, 51(11): 640-644.
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[5] Nguang S K, Shi P. Fuzzy H_∞ output feedback control of nonlinear systems under sampled measurements [J]. Automatica, 2003, 39(12): 2169-2174.
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[8] Peng C, Tian Y. Networked H_∞ control of linear systems with state quantization [J]. Information Sciences, 2007, 177(24): 5763-5774.
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Memo

Memo:

Biographies: Chu Hongyan(1979—), female, graduate; Fei Shumin(corresponding author), male, doctor, professor, smfei@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.60474049, 60835001), Specialized Research Fund for Doctoral Program of Higher Education(No.20090092120027).
Citation: Chu Hongyan, Fei Shumin, Chen Haixia, et al. T-S-fuzzy-model-based quantized control for nonlinear networked control systems[J]. Journal of Southeast University(English Edition), 2010, 26(1): 137-141.

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