Adaptive fuzzy backstepping control for a class of strict-feedback discrete-time nonlinear systems

被引：0

作者：

Wang, Xin ^{[1
]}

Li, Tieshan ^{[1
]}

Cai, Yao ^{[1
]}

Lin, Bin ^{[2
]}

机构：

[1] Dalian Martime Univ, Nav Coll, Dalian, Peoples R China

[2] Dalian Martime Univ, Dept Informat Sci & Technol, Dalian, Peoples R China

来源：

2014 11TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA) | 2014年

基金：

中国国家自然科学基金;

关键词：

discrete-time nonlinear systems; adaptive fuzzy control; minimal learning parameter (MLP); strict-feedback system; SMALL-GAIN APPROACH; TRACKING CONTROL; NEURAL-NETWORK; NN CONTROL; DISTURBANCES; DESIGN;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, by incorporating "minimal learning parameter (MLP)" technique into an adaptive fuzzy control design framework, a backstepping based control algorithem is presented for a class of uncertain strict-feedback nonlinear discrete-time systems. The proposed scheme is able to circumvent the problem of " curse of dimension" for high-dimensional systems. thus the number of parameters updated online for each subsystem is reduced to one, no matter how many rules are used in fuzzy systems and how many input variables exist in the system. Takagi-Sugeno (T-S) fuzzy systems are used to approximate the unknown system functions. It is shown via Lyapunov theory that all signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). Finally, a simulation example is employed to illustrate the effectiveness and advantages of the proposed scheme.

引用

页码：261 / 266

页数：6

共 25 条

[1] Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping approach [J].

Chen, Bing ;

Tong, Shaocheng ;

Liu, Xiaoping .

FUZZY SETS AND SYSTEMS, 2007, 158 (10) :1097-1125

[2] Adaptive fuzzy output tracking control of MIMO nonlinear uncertain systems [J].

Chen, Bing ;

Liu, Xiaoping ;

Tong, Shaocheng .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2007, 15 (02) :287-300

[3] ADAPTIVE-CONTROL OF A CLASS OF NONLINEAR DISCRETE-TIME-SYSTEMS USING NEURAL NETWORKS [J].

CHEN, FC ;

KHALIL, HK .

IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1995, 40 (05) :791-801

[4] Adaptive Backstepping Fuzzy Control for Nonlinearly Parameterized Systems With Periodic Disturbances [J].

Chen, Weisheng ;

Jiao, Licheng ;

Li, Ruihong ;

Li, Jing .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2010, 18 (04) :674-685

[5] Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints [J].

Chen, Weisheng .

ISA TRANSACTIONS, 2009, 48 (03) :304-311

[6] A survey on analysis and design of model-based fuzzy control systems [J].

Feng, Gang .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2006, 14 (05) :676-697

[7] An improved stable adaptive fuzzy control method [J].

Fischle, K ;

Schröder, D .

IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1999, 7 (01) :27-40

[8] Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems (vol 39, pg 807, 2003) [J].

Ge, S. S. ;

Li, G. Y. ;

Lee, T. H. .

AUTOMATICA, 2008, 44 (07) :1930-1931

[9] Adaptive predictive control using neural network for a class of pure-feedback systems in discrete time [J].

Ge, Shuzhi Sam ;

Yang, Chenguang ;

Lee, Tong Heng .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2008, 19 (09) :1599-1614

[10] Adaptive neural network control for a class of MIMO nonlinear systems with disturbances in discrete-time [J].

Ge, SS ;

Zhang, J ;

Lee, TH .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (04) :1630-1645

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