|Table of Contents|

Construction equipment on energy-saving control strategy

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2014年01期
Page:
54-58
Research Field:
Publishing date:

Info

Title:
Construction equipment on energy-saving control strategy
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
Keywords:
variable air volume air conditioning improved elman neural network T-S fuzzy recursive neural network predictive control decoupling control
PACS:
TP273
DOI:
-
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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Last Update: 2014-02-28