Application of neural networks and genetic algorithm in knowledge acquisition of fuzzy control system

被引：0

作者：

Wang, Shuqing ^{[1
]}

Liao, Jiaping ^{[1
]}

Zhang, Zipeng ^{[2
]}

Yuan, Xiaohui ^{[2
]}

机构：

[1] Hubei Univ Technol, Sch Elect & Elect Engn, Wuhan, Hubei, Peoples R China

[2] Huazhong Univ Sci & Technol, Sch Hydro Power & Digitalizat Engn, Wuhan, Peoples R China

来源：

WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年

关键词：

fuzzy control; RBF neural networks; genetic algorithm; hydroelectric generating unit; optimal control;

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：

Often it is difficult to acquire the requisite knowledge in the design of rule-based control systems. In the study, an advanced knowledge acquisition technique was used to optimize fuzzy controller in the control of hydroelectric generating unit system of hydropower plant. The designed control system may select optimal scale factors, membership functions and control rules efficiently by using neural networks and genetic algorithm. Genetic algorithm was used to optimize the parameters and rules of fuzzy controller in operating. Dynamic identification model of control system based on RBF neural networks was designed to appraise the controlling performance of fuzzy controller. Simulation results show that the advanced knowledge acquisition technique makes scale factors, membership functions and control rules of fuzzy controller arrive to optimization and its control performance is superior to conventional controller.

引用

页码：3886 / +

页数：2

共 50 条

[41] Manipulator Neural Network Control Based on Fuzzy Genetic Algorithm
崔平远
High Technology Letters, 2001, (01) : 63 - 66
[42] Adaptive Fuzzy Neural Network Control Based on Genetic Algorithm
Chen, Jian
2021 13TH INTERNATIONAL CONFERENCE ON MEASURING TECHNOLOGY AND MECHATRONICS AUTOMATION (ICMTMA 2021), 2021, : 393 - 396
[43] Application of a system for the automatic generation of fuzzy neural networks
Liao, J
Er, MJ
Lin, JY
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2000, 13 (03) : 293 - 302
[44] The application of fuzzy control in the hoist constant deceleration braking system based on genetic algorithm
Liu, J. Y.
Zou, Y. M.
2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 1, 2008, : 569 - 573
[45] Application of fuzzy control method on neural networks in the armored vehicle electric drive system
Li, H
Ma, XJ
Zhang, YN
Zhang, J
Liu, ZX
ISTM/2005: 6th International Symposium on Test and Measurement, Vols 1-9, Conference Proceedings, 2005, : 1225 - 1228
[46] DUAL FUZZY NEURAL NETWORK ADAPTIVE CONTROL ON LEARNING AS AUTOMATION OF KNOWLEDGE ACQUISITION
Xu, Kaijun
Wei, Menghan
Pan, Xiaodong
Qin, Keyun
COMPUTATIONAL INTELLIGENCE: FOUNDATIONS AND APPLICATIONS: PROCEEDINGS OF THE 9TH INTERNATIONAL FLINS CONFERENCE, 2010, 4 : 294 - +
[47] CMAC neural networks and PID concurrent control algorithm and its application to nonlinear system control
Zhang, MG
Liu, MQ
Li, WH
Proceedings of the 11th Joint International Computer Conference, 2005, : 459 - 463
[48] Fuzzy control of a chaotic system based on genetic algorithm
Wu, ZQ
Ao, D
Liu, K
ACTA PHYSICA SINICA, 2004, 53 (01) : 21 - 24
[49] Fuzzy Optimization of an Elevator Mechanism Applying the Genetic Algorithm and Neural Networks
XI Ping-yuan1
International Journal of Plant Engineering and Management, 2005, (04) : 236 - 240
[50] Genetic programming and bacterial algorithm for neural networks and fuzzy systems design
Cabrita, C
Botzheim, J
Ruano, AE
Kóczy, LT
INTELLIGENT CONTROL SYSTEMS AND SIGNAL PROCESSING 2003, 2003, : 443 - 448

← 1 2 3 4 5 →