|本期目录/Table of Contents|

[1]胥 良,郭 林,梁 亚,等.基于模糊RBF神经网络的智能PID控制[J].工业仪表与自动化装置,2015,(06):67.
　XU Liang,GUO Lin,LIANG Ya,et al.Study on intelligent PID control based on fuzzy RBF neural network[J].Industrial Instrumentation & Automation,2015,(06):67.
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基于模糊RBF神经网络的智能PID控制(PDF)

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2015年06期
页码:
67
栏目:
出版日期:
2015-12-15

文章信息/Info

Title:
Study on intelligent PID control based on fuzzy RBF neural network
文章编号:
1000-0682（2015）06-0000-00
作者:
胥 良; 郭 林; 梁 亚; 杨金龙; 张卫芳
（黑龙江科技大学 电气与控制工程学院，哈尔滨 150022）
Author(s):
XU Liang;  GUO Lin;  LIANG Ya;  YANG Jinlong;  ZHANG Weifang
(Electrical and Control Engineering, Heilongjiang University of Science and Technology, Haerbin 150022, China)
关键词:
神经网络; 模糊算法; PID
Keywords:
RBF neural NN;  fuzzy algorithm;  PID
分类号:
TP183
DOI:
-
文献标志码:
A
摘要:
针对常规PID控制参数变化系统效果不佳的缺点，设计一种利用智能控制理论RBF神经网络与模糊控制技术相融合的新型智能PID控制方法[1]。该控制方法将系统的输入误差及其变化率进行模糊化后，再利用RBF神经网络算法对PID控制参数进行在线学习、运算和整定[2]。并通过MATLAB仿真，结果表明基于上述的PID控制方法能够克服传统PID控制器的局限性，具有较高的控制精度，较好的动态品质及较强的鲁棒性。
Abstract:
Aiming at the shortcoming of traditional PID control, a method which combines a RBF neural network with fuzzy control is designed[1]. Carry on fuzzy processing to system output error and the rate of error change. Learn、operate and set PID control coefficient using RBF neural network online[2].Through the MATLAB simulation，the result shows that the PID control algorithm based on the former algorithm can overcome the limitations of traditional PID controller, with higher control accuracy, better dynamic quality and more powerful robustness.

参考文献/References:

[1] Jian Liu, Wen-Jian Cai,Gui-Qing,et al. Design and Application of Handheld Auto-tuning PID Instrument Used in VAC[C]. Proceedings of the 4th IEEE Conference on Industrial Electronics and applications, Xi’an, hina, May, 2009: 1695-1698.

[2] Hong-Li Lv, Pei-Yong Duan. A Novel Fuzzy Controller Design Based-on PID Gains for HVAC Systems[C]. Proceedings of the 7th World Congress on Intelligent Control and Automation , Chongqing, China ,June, 2008:25-27.
[3] Ming-guang Zhang, Wen-hui Li, Man-qing Liu .A daptive PID Control Strategy Based on RBF Neural Network Identification[G ].IEEE 2005:1854-1857.
[4] 启宏杰,尔联洁,刘强,陈敬泉.基于神经网络自适应稳定PID控制方法的研究[J].北京航空航天大学学报,2001, 27(2):153-156.
[5] 戴葵,译.神经网络设计[M].北京:机械工业出版社,2002: 99-181.

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备注/Memo

备注/Memo:
收稿日期：2015-03-20
基金项目：黑龙江省教育厅科研面上项目“矿井交流提升机调速控制策略的研究及应用”（11541321）
作者简介：胥良（1966），男，黑龙江省牡丹江人，教授，硕士，研究方向为煤矿安全检测与控制。
更新日期/Last Update: 1900-01-01