Networked fuzzy output feedback control for discrete-time Takagi-Sugeno fuzzy systems with sensor saturation and measurement noise

被引:30
作者
Zhang, Dawei [1 ]
Zhou, Zhiyong [1 ]
Jia, Xinchun [1 ]
机构
[1] Shanxi Univ, Sch Math Sci, Taiyuan 030006, Peoples R China
基金
中国国家自然科学基金;
关键词
Networked fuzzy static output feedback control; Sensor saturation; A discrete-time asynchronous T-S fuzzy system; An augmented fuzzy Lyapunov-Krasovskii functional; H-INFINITY STABILIZATION; LMI-BASED APPROACH; STABILITY ANALYSIS; DESIGN; INEQUALITY; DELAY; CRITERION; SUBJECT;
D O I
10.1016/j.ins.2018.02.026
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper deals with the problem of networked fuzzy static output feedback control for discrete-time Takagi-Sugeno fuzzy systems with sensor saturation and measurement noise. First, by taking network-induced delays and packet dropouts into account, the resulting closed-loop fuzzy system is modeled as an asynchronous discrete-time T-S fuzzy system subject to both interval-like delays and sector nonlinearity. Second, an augmented fuzzy basis-dependent Lyapunov functional is introduced. By employing a matrix-based quadratic convex method, an interval-delay-dependent bounded real lemma is derived such that the closed-loop system has a prescribed H-infinity performance level. Third, a fuzzy controller design method is presented by using a cone complementarity linearization algorithm. Finally, a nonlinear inverted pendulum system via networked fuzzy control is provided to show that the proposed results are of less conservatism and exhibit satisfactory adaptability to sensor saturation. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:182 / 194
页数:13
相关论文
共 46 条
[11]   Design of robust-optimal output feedback controllers for linear uncertain systems using LMI-based approach and genetic algorithm [J].
Ho, Wen-Hsien ;
Chen, Shinn-Horng ;
Liu, Tung-Kuan ;
Chou, Jyh-Horng .
INFORMATION SCIENCES, 2010, 180 (23) :4529-4542
[12]   T-S fuzzy-model-based robust stabilization for a class of nonlinear discrete-time networked control systems [J].
Hu, Songlin ;
Zhang, Yunning ;
Yin, Xiuxia ;
Du, Zhaoping .
NONLINEAR ANALYSIS-HYBRID SYSTEMS, 2013, 8 :69-82
[13]   A new H∞ stabilization criterion for networked control systems [J].
Jiang, Xiefu ;
Han, Qing-Long ;
Liu, Shirong ;
Xue, Anke .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2008, 53 (04) :1025-1032
[14]  
Khalil H. K., 2000, Nonlinear Systems, V3rd
[17]   Relaxed H∞ Stabilization Conditions for Discrete-Time Fuzzy Systems With Interval Time-Varying Delays [J].
Kim, Sung Hyun ;
Park, PooGyeon .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2009, 17 (06) :1441-1449
[18]   An improved digital redesign for sampled-data fuzzy control systems: Fuzzy Lyapunov function approach [J].
Koo, Geun Bum ;
Park, Jin Bae ;
Joo, Young Hoon .
INFORMATION SCIENCES, 2017, 406 :71-86
[19]   Stability and stabilization of T-S fuzzy systems with time-varying delays via augmented Lyapunov-Krasovskii functionals [J].
Kwon, O. M. ;
Park, M. J. ;
Park, Ju H. ;
Lee, S. M. .
INFORMATION SCIENCES, 2016, 372 :1-15
[20]   A review on stability analysis of continuous-time fuzzy-model-based control systems: From membership-function-independent to membership-function-dependent analysis [J].
Lam, H. K. .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 67 :390-408