[1]周 鹏,陈 洋,官文越.建筑设备节能控制策略[J].南京理工大学学报(自然科学版),2014,38(01):54-58.
 Zhou Peng,Chen Yang,Guan Wenyue.Construction equipment on energy-saving control strategy[J].Journal of Nanjing University of Science and Technology,2014,38(01):54-58.
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建筑设备节能控制策略
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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:
38卷
期数:
2014年01期
页码:
54-58
栏目:
出版日期:
2014-02-28

文章信息/Info

Title:
Construction equipment on energy-saving control strategy
作者:
周 鹏12陈 洋2官文越2
1.大连交通大学 信息与控制工程学院,辽宁 大连 116021; 2.沈阳建筑大学 信息与控制工程学院,辽宁 沈阳 110168
Author(s):
Zhou Peng12Chen Yang2Guan Wenyue2
1.School of Information and Control Engineering,Dalian Jiaotong University,Dalian 116021,China; 2.School of Information and Control Engineering,Shenyang Jianzhu University,Shenyang 110168,China
关键词:
变风量空调 改进型Elman神经网络 T-S模糊递归神经网络 预测控制 解耦控制
Keywords:
variable air volume air conditioning improved elman neural network T-S fuzzy recursive neural network predictive control decoupling control
分类号:
TP273
摘要:
由于变风量空调控制系统具有非线性、大滞后、时变性的特点,该文提出了一种基于改进型Elman神经网络预测和改进型T-S模糊神经网络控制的结构,其预测输出与实际输出的差值作为T-S模糊神经网络控制器的输入,使空调控制系统具有较高的控制精度和良好的动态特性。由于变风量空调运行时各变量之间的耦合关系,又结合了解耦的控制方法,达到了抑制温度和湿度耦合的控制效果。仿真结果表明:与传统PID控制相比,该控制系统具有较强的鲁棒性,学习能力强,控制精度高,控制效果好,有较强的解耦控制能力。
Abstract:
As the variable air volume(VAV)control system has the nonlinearity,large time delay and time variation and other characteristics,this paper proposes a structure based on the modified Elman neural network prediction and the modified T-S fuzzy neural network control.The input of the T-S fuzzy neural network controller includes the error of the output of the prediction and the actual output,so that it has the high control precision,good dynamic characteristic.As each variable has the coupling relationship when the VAV system is running,it is combined with a decoupling control method to produce the effect that the temperature and humidity don't have the coupling relationship.The simulation results show that:comparing with the traditional PID control system,this control system has stronger robustness and stronger skills of learning,higher control precision,better control effect,stronger ability of decoupling control.

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备注/Memo

备注/Memo:
收稿日期:2013-03-03 修回日期:2013-06-03
基金项目:国家自然科学基金(51078241)
作者简介:周鹏(1980-),男,博士生,助理研究员,主要研究方向:建筑装备智能化,E-mail:zhoupeng0718@163.com。
引文格式:周鹏,陈洋,官文越.建筑设备节能控制策略[J].南京理工大学学报,2014,38(1):54-58.
投稿网址:http://njlgdxxb.paperonce.org
更新日期/Last Update: 2014-02-28