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International Journal of Fuzzy Systems

, Volume 20, Issue 6, pp 1790–1807 | Cite as

Fuzzy Inference Procedure for Intelligent and Automated Control of Refrigerant Charging

  • Issam Damaj
  • Jean Saade
  • Hala Al-Faisal
  • Hassan Diab
Article
  • 69 Downloads

Abstract

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.

Keywords

Refrigerant charging Modeling human expertise Performance Fuzzy inference LabVIEW 

Notes

Acknowledgements

The authors would like to thank Mr. M. El-Khalili, a Senior Mechanical Engineer and Market Area Director at Eberspcher Strak GmbH, Germany, for the help and advice he provided in some paper-related issues. In addition, the authors are grateful for the thorough reviews, by the editor and the anonymous reviewers, that enabled great improvements to this paper.

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Copyright information

© Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringAmerican University of KuwaitSalmiyaKuwait
  2. 2.Department of Electrical and Computer EngineeringAmerican University of BeirutBeirutLebanon
  3. 3.Department of Computer EngineeringKuwait UniversityKhaldiyaKuwait

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