Title :
An Improved Fuzzy RBF Based on Cluster and Its Application in HVAC System*
Author :
Li, Shujiang ; Zhang, Xiaoqing ; Xu, Jinxue ; Cai, Wenjian
Author_Institution :
Sch. of Inf. & Sci. Eng., Shenyang Univ. of Technol.
Abstract :
To solve the existing problems in modeling the HVAC (heating ventilating and air-conditioning) systems the paper proposed an improved algorithm based on fuzzy RBFNN (RBF neural networks). First, the sampling data of the HVAC system are processed using the improved fuzzy clustering method so as to redescribe the fuzzy space, thus obtaining the number of hidden layers and its parameters. Then the least square method is used to find the weights between the hidden layer and the output layer. At last, the parameters are revised by the steepest gradient descent method. Experiments demonstrated the proposed algorithm could accurately identify the model of HVAC systems even in the face of strong disturbance and system coupling. Moreover, the model outputs could track the actual outputs
Keywords :
HVAC; fuzzy neural nets; gradient methods; least squares approximations; radial basis function networks; HVAC system; RBFNN; air-conditioning system; fuzzy RBF neural network; fuzzy clustering; fuzzy space; gradient descent method; heating system; least square method; radial basis function; system coupling; ventilating system; Clustering algorithms; Cooling; Ducts; Educational technology; Energy consumption; Fuzzy systems; Mathematical model; Neural networks; Paper technology; Temperature control; Cluster; HVAC; RBF neural network;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1714328
