Robust sampled-data control for nonlinear systems based on T-S fuzzy model

被引：0

作者：

Lian H.-H. ^{[1
]}

Deng P. ^{[1
]}

Xiao S.-P. ^{[2
]}

Xiao H.-Q. ^{[2
]}

机构：

[1] School of Wind Energy Engineering, Hunan Electrical College of Technology, Xiangtan, 411101, Hunan

[2] School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou, 412008, Hunan

来源：

Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2020年 / 37卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Lyapunov functional; Nonlinear systems; Robust stabilization; Sampled-data control; T-S fuzzy model;

D O I：

10.7641/CTA.2020.90413

中图分类号：

学科分类号：

摘要：

The problem of robust stabilization for a class of nonlinear systems, which is described as Takagi-Sugeno (T-S) fuzzy model, is investigated through the use of fuzzy sampled-data control method. Firstly, by taking full advantage of characteristic information on the whole sampling interval [tk, tk+1), a improved two-side time-dependent Lyapunov functional is constructed. Furthermore, with the presented Lyapunov functional and free-matrix-based inequality, a robust stabilization criterion is derived to guarantee the asymptotic stability for nonlinear systems, and the fuzzy sampled-data controller design approach is also proposed. Finally, four simulation examples are given to verify the effectiveness and superiority of the proposed method. © 2020, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.

引用

页码：1601 / 1610

页数：9

共 26 条

[1]

LIAN K, CHIU C, CHIANG S, Et al., Secure communications of chaotic systems with robust performance via fuzzy observer-based design, IEEE Transactions on Fuzzy Systems, 9, 1, pp. 212-220, (2001)

[2]

BOUZERIBA A, BOULKROUNE A, BOUDEN T., Projective synchronization of two different fractional-order chaotic systems via adaptive fuzzy control, Neural Computing & Applications, 27, 5, pp. 1349-1360, (2016)

[3]

XIAO Huiqin, HE Yong, WU Min, Et al., Improved H1 tracking control for nonlinear networked control systems based on T-S Fuzzy model, Control Theory & Applications, 29, 1, pp. 71-78, (2012)

[4]

CHANG X H, YANG G H., Relaxed stabilization conditions for continuous-time Takagi-Sugeno fuzzy control systems, Information Sciences, 180, 17, pp. 3273-3287, (2010)

[5]

PARK J H, KWON O M., A novel criterion for delayed feedback control of time-delay chaotic systems, Chaos, Solitons & Fractals, 23, 2, pp. 495-501, (2005)

[6]

ZTIBI M, SMAOUI H, SALIM H., Synchronization of the unified chaotics systems using a sliding mode controller, Chaos, Solitons & Fractals, 42, 15, pp. 3197-3209, (2009)

[7]

CHEN W H, LUO S, ZHENG W X., Generating globally stable periodic solutions of delayed neural networks with periodic coefficients via impulsive control, IEEE Transactions on Cybernetics, 47, 7, pp. 1590-1603, (2017)

[8]

XIAO Huiqin, HE Yong, WU Min, Et al., Non-fragile H1 tracking control for networked control systems based on T-S Fuzzy model, Control & Decision, 30, 1, pp. 110-116

[9]

LOIA V, TOMASIELLO S, VACCARO A., Fuzzy transform based compression of electric signal waveforms for smart grids, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47, 1, pp. 121-132, (2017)

[10]

LI H, JING X, LAM K, Et al., Fuzzy sampled-data control for uncertain vehicle suspension systems, IEEE Transactions on Cybernetics, 44, 7, pp. 1111-1126, (2014)

← 1 2 3 →