| 基于改进模糊神经网络的PID参数自整定算法 |
| |
| 引用本文： | 欧国徽,刘春波,潘丰.基于改进模糊神经网络的PID参数自整定算法[J].江南大学学报(自然科学版),2011,10(2):145-149. |
| |
| 作者姓名： | 欧国徽 刘春波 潘丰 |
| |
| 作者单位： | 江南大学轻工过程先进控制教育部重点实验室,江苏无锡,214122 |
| |
| 摘 要： | 针对传统的PID控制算法参数整定困难,控制效果并不理想,将神经网络算法、模糊控制算法结合在一起,形成了模糊神经网络PID参数自整定算法,并且对模糊神经网络进行改进,将神经网络输入的状态变量进行模糊化和归一化处理,采用BP神经网络自整定PID控制器的参数,根据RBF神经网络得到受控对象的Jacobian信息。仿真结果表明,基于模糊神经网络的PID自整定控制效果较好,具有一定的应用前景。
|
| 关 键 词： | PID控制算法 神经网络 模糊控制 自整定 |
Self-Tuning of PID Parameter Algorithm Based on Improved Fuzzy Neural Networks |
| |
| OU Guo-hui,LIU Chun-bo,PAN Feng.Self-Tuning of PID Parameter Algorithm Based on Improved Fuzzy Neural Networks[J].Journal of Southern Yangtze University:Natural Science Edition,2011,10(2):145-149. |
| |
| Authors: | OU Guo-hui LIU Chun-bo PAN Feng |
| |
| Institution: | OU Guo-hui,LIU Chun-bo,PAN Feng(Key Laboratory of Advanced Process Control for Light Industry,Ministry of Education,Jiangnan University,Wuxi 214122,China) |
| |
| Abstract: | For traditional PID parameter tuning difficulties,control effect is not ideal.This paper addresses this issue.Fuzzy control algorithms and neural network algorithms are combined to form an FNN self-tuning of PID parameter algorithm.Besides,some improvement based on FNN normalization and obfuscation is made to deal with the input state variables of Neural Networks.BP Neural Network is used to adaptively adjusts PID parameters.Using RBF Neural Network get plant's Jacobian information.The experimental results ... |
| |
| Keywords: | PID control algorithm fuzzy control neural network self-tuning |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
