The Control of BP-PID Neural Network Based on PSO and Its Application
When using tradition PID. it is digcult to confirm the PID parameters and has long settling time. However when using BP-PID method, it produces over-fitting to initial assignments, local optimum induced easily and slow convergence rate problem. Based on the global optimization feature of particle swarm optimization algorithm, it has been adopted to optimize the connect values of BP-PID neural network in this paper. An intelligent control algorithm is put forward based on BP-PID neural network optimized by particle swarm optimization algorithm. Then it is operated and debugged on emulation mode. The experiment result proves that the method, parameters self-regulation, good robustness, shorter adjustment time and faster response time, better quality of control.
particle swarm optimia.on algorifhm neural network BP- PID control emulation
Fang Ding Maowei Qiao Chunguo Fei
Aeronautical Automation College, Civil Aviation University of China,Tianjin, China
国际会议
成都
英文
191-195
2010-12-17（万方平台首次上网日期，不代表论文的发表时间）