# A Review on Applications of Fuzzy Logic Control for Refrigeration Systems
## 3 Fuzzy Driver Applications on RACs
### Fuzzy Control in Chillers and Cold Rooms  
Chillers are one of the RACs in which the fuzzy logic control systems have been applied with interesting results. For instance, the integration with other control strategies allows to improve the operating conditions and obtain energy savings. In this sense, [PERSON] et al. [26] found that it was possible to improve energy efficiency by 1% and have more stable thermal conditions through diffuse PD + I control, regulating the frequency and acceleration of the compressor. [PERSON] et al. [27] implemented a fuzzy PID controller and a fuzzy PI controller and found that the fuzzy PID controller was better adapted to the cooling system by presenting better performance, responding to fluctuations in the thermal load, and reducing the error by 43% in the set point.  
On the other hand, comparative studies have shown that fuzzy control allows for the obtaining of better results compared to conventional controllers. In this sense, [PERSON] and [PERSON] [28] carried out a comparative study between thermostatic control and diffuse control for a chiller that works with a variable-speed compressor and an expansion solenoid  
Figure 3: General scheme of a PID-fuzzy controller.  
value, and found that the diffuse controller reduced energy consumption by 17%. In a later study, a fuzzy control, a PID control, and a neural network control were compared; the results indicate that fuzzy control can reduce energy consumption by 1.4% compared to PID control, while fuzzy control consumes 6.6% more than neural network control [29]. [PERSON] et al. [30] proposed a self-adjusting fuzzy controller to improve the performance of cooling systems; in addition, they compared a PID control and fuzzy control. They determined that the self-adjusting fuzzy controller improves thermal performance by reducing thermal inertia compared to the other controllers tested. These studies show the advantages that fuzzy controllers offer compared to PID controllers, mainly more stable temperature control is allowed so that reductions in power consumption can be achieved. Additionally, the integration of fuzzy logic and fuzzy PID controllers allows for better results than implementing each controller.  
[PERSON] et al. [31] presented a fuzzy control algorithm for the temperature of a cold room; they regulated the speed of the compressor to evaluate energy savings. In addition, they evaluated two working fluids, R40/C and R507, as substitutes for the R22 refrigerant. The authors found that diffuse control showed 13% energy savings compared to conventional thermostatic control using R40/C refrigerant. [PERSON] et al. [32] relied on the coupling of temperature and humidity for the development of the fuzzy controller, concluding that the fuzzy controller had a suitable design for the dynamic behavior of the process. [PERSON] et al. [33] found the fuzzy controller as a simple solution for the overheating regulation problem of an industrial refrigeration plant. They regulated the opening of the expansion valve and determined that the controller had the flexibility to implement subjective solutions, as well as being a practical and cost-effective alternative to conventional control methods.  
Fuzzy control strategies have been shown to improve the conditions in the control of variables [25; 31] and on some occasions, it has even been possible to reduce energy consumption [27; 30]. To achieve these energy savings, several factors intervene, such as the number of controlled variables, the type of actuators, and considerations in the design of the controllers. In this sense, [PERSON] et al. [33] found that multivariate control is more efficient in controlling temperature, but less efficient in energy consumption, compared to one-variable control. Therefore, control strategies attempt to find a balance between being able to meet control objectives and achieving energy savings.