# A Review on Applications of Fuzzy Logic Control for Refrigeration Systems
## 3 Fuzzy Driver Applications on RACs
### Fuzzy Control in Air Conditioning Systems
[44] proposed a fuzzy genetic algorithm that reduced annual energy consumption by 36%, in which compressor speed, fan speed, and damper opening (Do) were regulated. All of these parameters were adjusted to control temperature, air supply, and CO\({}_{2}\) concentration. [PERSON] et al. [45] predicted the internal temperature of a building using an autoregressive neural network with external inputs. This internal temperature served as input for the fuzzy control system that controlled the ON/OFF of an air conditioning system. The combination of a neuro-fuzzy control yielded adequate results because of the dynamic regulation of the ON/OFF of the air conditioning system. [PERSON] et al. [46] improved the efficiency of a system based on the variation of human comfort, as well as relative humidity and dew point. They found that fuzzy control had great feasibility to be implemented in a real system. [PERSON] et al. [47] proposed the integration between a diffuse control and an ON/OFF control for a residential building. The proposal was made to improve the operation of an ON/OFF control taking into consideration the incident solar radiation in the building. Thus, fuzzy controllers can be perfectly coupled to those systems where, due to physical restrictions, they limit the variables that can be manipulated. Air conditioning systems are subject to a variety of variable conditions, such as weather parameters or variations in operating parameters. Therefore, fuzzy controllers perform best when a MIMO control system is considered and the interaction between temperature and humidity is taken into account. It is not only the use of the internal temperature of the space and the humidity as input variables for the diffuse control allow adequate thermal and energy results. Other variables, such as ambient temperature or refrigerant flow, among others, affect the behavior of the system. The inclusion of these types of variables in the fuzzy controller has also allowed for the obtaining of more efficient systems and achieving better control of the variables, mainly while achieving system stability. In this sense, [PERSON] and [PERSON] [48] succeeded in improving the evaporator superheat (SH) of using an adaptive controller and consequently improved energy efficiency. [PERSON] et al. [49] developed a MIMO controller for a variable speed compressor taking into account the operating hours of the air conditioning system. The author found that fuzzy logic showed advantages in solving analytically complex problems, starting from intuitive knowledge and resulting in optimal performance. The study of air quality through CO\({}_{2}\) concentration is also considered in some studies. Between these, [PERSON] et al. [24] showed an expert control system for an HVAC controlling the amount of oxygen in a room and taking into account the outside ambient temperature. It was shown that the performance of this controller was better than the conventional controller, as it reduced the overshoot by 2.25%, provided precise control, and quickly adapted to diverse operating conditions. [PERSON] et al. [50] took into account CO\({}_{2}\) concentration, in addition to the traditional variables for control, obtaining higher and more stable responses than traditional control algorithms. The above shows that the use of new types of controllers is focused not only on improving performance but also on improving conditions to maintain environments that do not harm health. On the other hand, the predicted mean vote, PMV, introduced by [PERSON] [51], is used to predict the thermal sensation on a standard scale based on environment variables, such as air temperature, radiance temperature, airspeed, and relative humidity. Additionally, other personal parameters, such as the activity level or cloth insulations were also considered. Some authors have included this factor in the design of diffuse control systems as an alternative for direct regulation of temperature and humidity. For instance, [PERSON] et al.