计算机工程与应用2012，Vol.48Issue(16)：233-236,4.DOI:10.3778/j.issn.1002-8331.2012.16.052
基于RBF神经网络与Smith预估补偿的智能PID控制
Intelligent PID control based on RBF neural network and Smith predictive compensation
王菲菲 1陈玮1
作者信息
- 1. 上海理工大学光电信息与计算机工程学院,上海200093
- 折叠
摘要
Abstract
Aiming at the phenomena of big time delay are normally exist in industry control, this paper proposes an intelligent RBF-Smith-PID control based on RBF neural network algorithm and Smith predictive compensation algorithm and traditional PID controller. This method uses the ability of online-study, a self-turning control strategy of RBF neural network, and better control of Smith predictive compensation to deal with the big time delay, overcome the limitation of traditional PID control effectively, improve the system's robustness and self-adaptability, get satisfactory control to deal with the big time delay system.关键词
纯滞后/神经网络/Smith预估控制/PID控制Key words
time-delay/ neural network/ Smith predictive control/ PID control分类
信息技术与安全科学引用本文复制引用
王菲菲,陈玮..基于RBF神经网络与Smith预估补偿的智能PID控制[J].计算机工程与应用,2012,48(16):233-236,4.
