Identification of fuzzy model of refrigerant condenser via Adaptive-Neuro-Fuzzy Inference System in vapour compression air conditioning system
by Jagdev Singh, Nirmal Singh, J.K. Sharma
International Journal of Automation and Control (IJAAC), Vol. 4, No. 2, 2010

Abstract: In this article, fuzzy model has been identified to study the effect of refrigerant flow and condenser temperature on condenser superheat. Fuzzy model of two input variables, mass flow rate and condenser temperature, one output variable condenser superheat was developed to describe its significance in vapour compression air conditioning system. Adaptive Neuro-Fuzzy Inference System (ANFIS) was used to study the trend of condenser superheat depending upon condensing temperature and refrigerant mass flow rate. To develop an effective Multi Input Single Output (MISO) model, fuzzy rule base was designed for vapour compression air conditioning system. The effect of input parameters on condenser superheat through the developed fuzzy model was studied. Simulation of fuzzy and mathematical model was carried which showed that the MISO control can significantly improve the superheat behaviour at the condenser pressure and hence energy efficiency of vapour compression refrigeration cycle.

Online publication date: Wed, 06-Jan-2010

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