[1]宋国庆,王书满,杨旭东.基于T-S模型的局部通风机风量模糊预测控制算法[J].南京理工大学学报(自然科学版),2017,41(05):591.[doi:10.14177/j.cnki.32-1397n.2017.41.05.009]
 Song Guoqing,Wang Shuman,Yang Xudong.Fuzzy predictive control algorithm of partial ventilatorbased on T-S model[J].Journal of Nanjing University of Science and Technology,2017,41(05):591.[doi:10.14177/j.cnki.32-1397n.2017.41.05.009]
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基于T-S模型的局部通风机风量模糊预测控制算法()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年05期
页码:
591
栏目:
出版日期:
2017-10-31

文章信息/Info

Title:
Fuzzy predictive control algorithm of partial ventilatorbased on T-S model
文章编号:
1005-9830(2017)05-0591-05
作者:
宋国庆1王书满2杨旭东2
1.江苏城市职业学院 机电工程学院,江苏 徐州 221006; 2.中国矿业大学 机电工程学院,江苏 徐州 221116
Author(s):
Song Guoqing1Wang Shuman2Yang Xudong2
1.Mechanical and Electrical Engineering College,Jiangsu Urban Vocational College,Xuzhou 221006,China; 2.Mechanical and Electrical Engineering College,China Mining University,Xuzhou 221116,China
关键词:
局部通风机 T-S模糊模型 聚类实验 预测控制
Keywords:
partial ventilators T-S fuzzy model clustering experiment predictive control
分类号:
TP274
DOI:
10.14177/j.cnki.32-1397n.2017.41.05.009
摘要:
针对目前比例-积分-微分(PID)控制、模糊控制以及模糊自适应PID控制方法在局部通风机风量控制系统中的不足,提出一种基于T-S模型的局部通风机风量模糊预测控制算法。首先建立了局部通风机系统的T-S模糊模型,并进行拟合度验证实验,然后提出基于T-S模型的模糊预测控制算法局部通风机风量控制策略,并对算法进行了实验验证。结果显示,局部通风系统中,该控制算法相对于PID控制、模糊控制以及模糊自适应PID控制具有更好的控制效果,并且该算法能够根据瓦斯的历史浓度做出先见性的控制。
Abstract:
Aiming at the shortness of proportion-integration-differentiation(PID)control,the fuzzy control and fuzzy adaptive PID control method in the partial ventilator system,a fuzzy predictive control algorithm based on the Takagi-Sugeno(T-S)model is proposed here.First,the T-S fuzzy model of the partial ventilator is established and the fitting degree validation experiment is carried out.Then,the fuzzy predictive ventilation control algorithm of the partial ventilator based on the T-S model is proposed.Finally,the algorithm is verified experimentally.Experimental results show that,compared with the PID control,the fuzzy control and the fuzzy adaptive PID control in the partial ventilator system,the control algorithm in this paper has the better performance and it can make the seer control according to the historical concentration of the gas.

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备注/Memo

备注/Memo:
收稿日期:2016-11-09 修回日期:2017-01-28
作者简介:宋国庆(1963-),男,副教授,主要研究方向:电气控制,E-mail:sgq5722116@126.com。
引文格式:宋国庆,王书满,杨旭东.基于T-S模型的局部通风机风量模糊预测控制算法[J].南京理工大学学报,2017,41(2):591-595.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-09-30