TY - JFULL AU - Mohanad Alata and Moh'd Al-Nimr and Rami Al-Jarrah PY - 2012/12/ TI - Fuzzy Control of the Air Conditioning System at Different Operating Pressures T2 - International Journal of Mechanical and Mechatronics Engineering SP - 2479 EP - 2486 VL - 6 SN - 1307-6892 UR - https://publications.waset.org/pdf/4654 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 71, 2012 N2 - The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases. ER -