Modeling and parameter identification of fresh air system based on ANFIS

A fresh air system with solar collectors and Latent Heat Thermal Storage (LHTS) tank filled with Phase Change Material was firstly introduced in this paper. For the mathematical model of the fresh air system is difficult to accurately establish, the adaptive neuro-fuzzy inference controller was proposed to realize the parameter identifications of the system applying for the back-propagation algorithm of BP neural network. The results shows that the modeling and parameter identification method of the algorithm using ANFIS can approximate the characteristics of the fresh air system to a great extent, and the error is almost zero.