A fuzzy-neural adaptive control for MIMO nonlinear system with application

被引：0

作者：

Piao, YG ^{[1
]}

Yang, ZQ ^{[1
]}

Li, YQ ^{[1
]}

Li, M ^{[1
]}

He, XQ ^{[1
]}

机构：

[1] HiSense Grp, Ctr Technol, Qingdao 266071, Peoples R China

来源：

PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5 | 2000年

关键词：

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, the fuzzy identification proposed by Takaki and Sugeno [1] is extended to the MIMO adaptive controller based on a hybrid neural network structure. The network is roughly divided into the premise and consequence corresponding to the T-S model. Each parameter of the consequence function Is convenient to be adjusted by the extended Bp algorithm so that automatic rule modification can be realized. The membership function of each fuzzy subset can be modified by genetic: algorithm (GA). In this way, the more pre-knowledge for plant need not required. Finally, the MIMO fuzzy-neural control is used to simulation of a real example.

引用

页码：935 / 939

页数：5

共 50 条

[21] Robust adaptive fuzzy-neural controllers for uncertain nonlinear systems [J].

Leu, YG ;

Wang, WY ;

Lee, TT .

IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, 1999, 15 (05) :805-817

[22] Online adaptive control of bandsaw feed speed using a fuzzy-neural system [J].

Sandak, J ;

Tanaka, C .

FOREST PRODUCTS JOURNAL, 2003, 53 (06) :36-43

[23] Application research of adaptive fuzzy neural controller for MIMO system [J].

Wang, Yan-Qiu ;

Wang, Jian-Hui ;

Gu, Shu-Sheng ;

Zhu, Yan-Feng .

Kongzhi yu Juece/Control and Decision, 2004, 19 (05) :577-581

[24] Adaptive fuzzy control for MIMO nonlinear system with unmodeled dynamics [J].

Liu, Wenxin ;

Wang, Huanqing ;

Qian, Weiyi .

ICIC Express Letters, 2016, 10 (09) :2157-2163

[25] Fuzzy-neural network adaptive sliding mode tracking control for interconnected system [J].

Zhang, Yan-xin ;

Dong, Hai-rong .

COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS, 2006, 4114 :127-133

[26] Fuzzy-neural adaptive controller design: with application to multiple-link robot control [J].

Hsu, YC ;

Chen, GR ;

Malki, HA .

1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, 1997, :1705-1709

[27] Fuzzy-Neural Adaptive Iterative Learning Control for a Class of Nonlinear Discrete-Time Systems [J].

Wang, Ying-Chung ;

Chien, Chiang-Ju .

2012 INTERNATIONAL CONFERENCE ON FUZZY THEORY AND ITS APPLICATIONS (IFUZZY2012), 2012, :101-106

[28] Adaptive fuzzy-neural control with state observer for unknown nonlinear systems via H∞ approaches [J].

Ho, HF ;

Wong, YK ;

Rad, AB .

ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE, 2002, :1877-1881

[29] Output-feedback control of nonlinear systems using direct adaptive fuzzy-neural controller [J].

Wang, WY ;

Leu, YG ;

Lee, TT .

FUZZY SETS AND SYSTEMS, 2003, 140 (02) :341-358

[30] Recurrent Fuzzy-Neural MIMO Channel Modeling [J].

Sarma, Kandarpa Kumar ;

Mitra, Abhijit .

JOURNAL OF INTELLIGENT SYSTEMS, 2012, 21 (02) :121-142

← 1 2 3 4 5 →