  Fuzzy logic controllers are readily customizable in natural language terms
and can effectively deal with nonlinearities and uncertainties in control
systems. This paper presents an intelligent and automated fuzzy control
procedure for the refrigerant charging of refrigerators. The elements that
affect the experimental charging and the optimization of the performance of
refrigerators are fuzzified and used in an inference model. The objective is to
represent the intelligent behavior of a human tester and ultimately make the
developed model available for the use in an automated data acquisition,
monitoring, and decision-making system. The proposed system is capable of
determining the needed amount of refrigerant in the shortest possible time. The
system automates the refrigerant charging and performance testing of parallel
units. The system is built using data acquisition systems from National
Instruments and programmed under LabVIEW. The developed fuzzy models, and their
testing results, are evaluated according to their compatibility with the
principles that govern the intelligent behavior of human experts when
performing the refrigerant-charging process. In addition, comparisons of the
fuzzy models with classical inference models are presented. The obtained
results confirm that the proposed fuzzy controllers outperform traditional
crisp controllers and provide major test time and energy savings. The paper
includes thorough discussions, analysis, and evaluation.
