RBF Neural Network Control System Optimized by Particle Swarm Optimization

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.

关键词： RBF neural network PSO nonlinear objects

作者: Xiucheng Dong Cong Wang Zhang Zhang

作者单位: Provincial key lab on signal and information processing, Xihua University Chengdu, China

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Computer Science and Information Technology(第三届IEEE计算机科学与信息技术国际会议 ICCSIT 2010)

会议地点: 成都

会议语种:英文

页码: 348-351

在线出版日期: 2010-07-07（万方平台首次上网日期，不代表论文的发表时间）