PID and fuzzy logic optimized controller for temperature control in a cavity of refrigeration

Jouda, Arfaoui; Feki, E.; Mami, Abdelkader

doi:10.1109/irec.2015.7110951

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…Azam and Mousavi [65] developed a controller for the temperature and humidity of a refrigerator; through simulation they verified that the fuzzy control saved operating costs and at the same time had fewer fluctuations in the internal temperature. Arfaoui et al [66] proposed an alternative method for the fuzzy controller, combining it with genetic algorithms and comparing it with the PID control. Using a third-order discrete-state system, they calculated the air temperature in the refrigerator and determined that the combination of genetic algorithms with fuzzy logic exhibited better thermal behavior and, consequently, the temperature of the setpoint was reached quickly, thus reducing energy consumption by 0.3957 kWh.…”

Section: Fuzzy Control In Domestic Refrigeratorsmentioning

confidence: 99%

A Review on Applications of Fuzzy Logic Control for Refrigeration Systems

et al. 2022

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The use of fuzzy logic controllers in refrigeration and air conditioning systems, RACs, has as main objective to maintain certain thermal and comfort conditions. In this sense, fuzzy controllers have proven to be a viable option for use in RACs due to their ease of implementation and their ability to integrate with other control systems and control improvements, as well as their ability to achieve potential energy savings. In this document, we present a review of the application of fuzzy controls in RACs based on vapor compression technology. Application information is discussed for each type of controller, according to its application in chillers, air conditioning systems, refrigerators, and heat pumps. In addition, this review provides detailed information on controller design, focusing on the potential to achieve energy savings; this design discusses input and output variables, number and type of membership functions, and inference rules. The future perspectives on the use of fuzzy control systems applied to RACs are shown as well. In other words, the information in this document is intended to serve as a guide for the creation of controller designs to be applied to RACs.

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Section: Fuzzy Control In Domestic Refrigeratorsmentioning

confidence: 99%

A Review on Applications of Fuzzy Logic Control for Refrigeration Systems

et al. 2022

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“…The authors concluded that the refrigerator exhibited a lower fluctuation in the internal temperature of the compartment, thereby achieving savings in operating costs. Arfaoui et al [28] proposed an alternative strategy to control the evaporator wall temperature and, consequently, the cavity interior temperature. Using fuzzy control and a combination of genetic algorithms, they compared the operation with a conventional Proportional Integral Derivative (PID) control.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Control Based on Usage Habits in a Domestic Refrigerator with Variable Speed Compressor for Energy-Saving

Belman-Flores,

Hernández-Fusilier,

García-Pabón

et al. 2024

Clean Technol.

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Maintaining adequate temperatures for preserving food in a domestic refrigerator is a task that is affected by several factors, including the daily use of the appliance. In this sense, this work presents the development of a novel control system based on fuzzy logic that considers usage habits such as the amount of food entering the refrigerator and the frequency of opening doors. Thus, the control comprises input variables corresponding to the internal temperatures of both compartments, the thermal load entered, and the refrigerator door-opening signal. By simulating the usage habits of a refrigerator with a variable-speed compressor, the control performance was evaluated. The results showed that implementing fuzzy control using usage habits was robust enough to maintain adequate thermal conditions within the compartments and a lower thermal fluctuation concerning the reference control of the refrigerator (factory control). In terms of energy, the fuzzy control resulted in an energy saving of 3.20% with the refrigerator empty (without thermal load) compared to the reference control. On the other hand, the individual integration of the thermal load in the fuzzy control resulted in 2.08% energy savings and 5.45% for the integration of the thermal load compared to the reference control. Finally, considering the combination of usage habits, the fuzzy control presented a higher energy consumption than the reference control, around 9.7%. In this case, the fuzzy control maintained more favorable thermal conditions in both compartments, whereas the reference control presented a warmer thermal condition in the freezer.

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