[1]佟世文.pH值系统变论域模糊控制器的设计及性能分析[J].智能系统学报,2011,6(04):367-372.
 TONG Shiwen.Design and performance analysis of a pH variable domain fuzzy control system[J].CAAI Transactions on Intelligent Systems,2011,6(04):367-372.
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pH值系统变论域模糊控制器的设计及性能分析(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第6卷
期数:
2011年04期
页码:
367-372
栏目:
学术论文—智能系统
出版日期:
2011-08-25

文章信息/Info

Title:
Design and performance analysis of a pH variable domain fuzzy control system
文章编号:
1673-4785(2011)04-0367-06
作者:
佟世文
中国天辰工程有限公司,北京 100029
Author(s):
TONG Shiwen
China Tianchen Engineering Corporation, Beijing 100029, China
关键词:
pH系统变论域实时模糊推理模糊控制器
Keywords:
pH system variable domain realtime fuzzy inference fuzzy controller
分类号:
TP273.4
文献标志码:
A
摘要:
针对pH值非线性控制系统,设计了一种实时简化变论域模糊控制器.将变论域思想与实时模糊推理策略相结合:一方面论域随着误差的减小而收缩,而论域的收缩相当于控制规则的增加,从而增加了控制精度;另一方面采用实时模糊推理方法,即对于一个二入一出的模糊控制器,一次推理过程中最多只激活4条控制规则,在控制的过程中只考虑这4条控制规则.这2种思想的结合使得控制规则的设计大大简化,可以采用批处理的方式设计控制器,不仅加快了系统的动态响应,也提高了控制精度.仿真结果证实了这种控制方法的有效性.
Abstract:
The realtime simplified variable domain fuzzy control method for the control of a pH nonlinear system was proposed. The method combined the idea of variable domain with the realtime fuzzy inference strategy. On the one hand, the method increased the control accuracy by the contraction of the domain following the decrease of errors, which is equivalent to the increase of the control rules. On the other hand, the algorithm activated at most four control rules during each control cycle by using the realtime fuzzy reasoning method for a typical twoinput oneoutput fuzzy controller. The consideration of the two ideas simplifies the design of the control rules, accelerates the dynamic response, and improves the control accuracy. The controller can be designed in a batch mode. The simulation results confirm that the method is effective.

参考文献/References:

[1]赵彦华,麻红昭. 一种用于pH值控制的非线性系统的实现[J]. 工业仪表与自动化装置, 2004, 3: 4043.
 ZHAO Yanhua, MA Hongzhao. A new nonlinear system designed for use with pH control[J]. Industrial Instrumentation & Automation, 2004, 3: 4043.
[2]HADJISKI M, BOSHNAKOV K, GALIBORA M. Neural networks based control of pH neutralization plant[C]//2002 First International IEEE Symposium on Intelligent Systems. Varna, Bulgaria, 2002: 712
[3]MUTHU R, KANZI E E. Fuzzy logic control of a pH neutralization process[C]//ICECS2003. Sharjah, United Arab Emirates, 2003: 10661069.
[4]RESENDE P, ZARALEGALVEZ L E. Control of a pH process using variable structure regulator and Smith predictor[C]//IECON’91. Kobe, Japan, 1991: 21022106.
[5]ALVAREZ T, TADEO F, GRIMBLE M J. Tuning of predictive controller using performance assessment measures: application to pH control[C]//Proceedings of the 2002 IEEE International Conference on Control Applications. Glasgow, UK, 2002: 403408.
[6]TONG S W, LIU G P. Realtime simplified variable domain fuzzy control of PEM fuel cell flow systems[J]. European Journal of Control, 2008, 14(3): 223233.
[7]侯传嘉,张燕群. pH值测量[M]. 北京: 中国计量出版社, 1993: 744.
[8]石红瑞,马智宏,孙洪涛. 基于多模型切换的pH自适应控制[C]//第五届全球智能控制与自动化大会. 杭州, 2004: 488491.
 SHI Hongrui, MA Zhihong, SUN Hongtao. pH adaptive control based on multiple model switching approach[C]//Proceedings of the 5th World Congress on Intelligent Control and Automation. Hangzhou, China, 2004: 488491.
[9]LI H X. Variable universe adaptive fuzzy controller[J]. Sci China Ser ETechnol Sci, 1999, 20: 3244.
[10]LI H X. Variable universe stable adaptive fuzzy control of a nonlinear systems[J]. Comput Math Appl, 2002, 44: 799815.
[11]HUANG Y, YU Y Q, ZENG T. A new realtime selfadaptive rule modification algorithm based on error convergence in fuzzy control[C]//IEEE Conference on Industrial Technology. Hong Kong, China, 2005: 789794.
[12]丛爽. 神经网络、模糊控制及其在运动控制中的应用[M]. 合肥:中国科学技术大学出版社, 2001: 86134.

备注/Memo

备注/Memo:
收稿日期:2009-12-01.
基金项目:国家自然科学基金资助项目(60774007).
通信作者:佟世文. E-mail: sun21st@sina.com.
 作者简介:佟世文,男,1976年生,高级工程师,博士,主要研究方向为欠驱动系统、网络化控制、燃料电池的建模与控制,发表学术文10余篇,获得发明专利一项.
更新日期/Last Update: 2011-09-30