工矿自动化2013，Vol.39Issue(6)：45-48,4.DOI:10.7526/j.issn.1671-251X.2013.06.012
基于BP神经网络的矿井提升机自校正容错PID控制
Self-tuning fault-tolerant PID control for mine hoist based on BP neural network
郭星歌 1吴娇娇 1刘静 1孙莉1
作者信息
- 1. 中国矿业大学信息与电气工程学院,江苏徐州221008
- 折叠
摘要
Abstract
In view of problem that traditional analysis method is difficult to obtain dynamic feature when mine hoist system failures,the paper proposed a self-tuning fault-tolerant PID control method for mine hoist based on BP neural network.The method employs BP neural network to predict system output value by learning and tracking dynamic features of the hoist system online,uses self-tuning neural network PID of self-adapt control to build fault-tolerant controller,so as to realize stable fault-tolerant control of the hoist system when fault happens.The simulation result shows that control method can track system fault state rapidly when a sudden fault happens,and adjust PID parameters online and restore system features in short time.关键词
矿井提升机/容错控制/自校正神经网络/PID控制/非线性系统Key words
mine hoist/ fault-tolerant control/ self-tuning neural network/ PID control/ nonlinear system分类
矿业与冶金引用本文复制引用
郭星歌,吴娇娇,刘静,孙莉..基于BP神经网络的矿井提升机自校正容错PID控制[J].工矿自动化,2013,39(6):45-48,4.
