RBF Neural Network Control System Optimized by Particle Swarm Optimization

被引：1
|
作者：
Dong, Xiucheng [1 ]
Wang, Cong [1 ]
Zhang, Zhang [1 ]
机构：
[1] Xihua Univ, Prov Key Lab Signal & Informat Proc, Chengdu, Peoples R China
来源：
ICCSIT 2010 - 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 3 | 2010年
关键词：
RBF neural network; PSO; nonlinear objects;
D O I：
10.1109/ICCSIT.2010.5563580
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A RBF neural network control system optimized by Particle Swarm Optimization is proposed. The control system was constructed by two RBF neural network, one was used as identifier and the other was used as controller. The system parameters were optimized by PSO, RBF neural network identified the nonlinear controlled object, the obtained Jacobian information used into RBF controller. Simulation results shows that the system optimized by PSO can get the ideal results of the control to the nonlinear objects, the system has good adaptive capacity and robustness.
引用
收藏
页码：348 / 351
页数：4
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