**3. Electrical control research for capacity-modulated refrigeration systems**

Any system, whose outputs are controlled by some inputs of the system, is called a control system. Electrical control techniques of the capacity-modulated refrigeration systems are very important, because of the quick response of the load changes. On/off control, proportionalintegral-derivative (PID), stochastic control, adaptive control, nonlinear methods, and robust control are known as conventional control systems. On/off and PID controls are the most commonly used methods in the heating ventilating and air-conditioning system control. Recent developments in artificial intelligence-based control systems have brought into focus a possibility of replacing control system with fuzzy logic control (FLC) equivalent. Therefore, fuzzy logic control is needed in the investigation on capacity-controlled refrigeration system. A standard PID controller is based on mathematical modeling of the system being controlled, whereas a fuzzy logic controls relies on physical rules rather than mathematical equations. In addition, fuzzy logic control provides a formal methodology for representing, manipulating, and implementing a human's heuristic knowledge about how to control a system.

Comparison of fuzzy logic and conventional controllers for a refrigeration system was investigated by Cheung and Kamal [73]. Fuzzy control application is realized on various compressor types following two authors. Aprea et al. [74] investigated fuzzy logic-based control algorithm which could select the most suitable compressor speed according to function of the cold store room air temperature. They found that this algorithm provides 13% energy saving when the R407C refrigerant was used at fuzzy logic-controlled variable speed reciprocating compressor. Furthermore, regarding the inverter cost, the payback period was more acceptable than for the examined cold storage plant.

Aprea and Mastrullo [75] investigated a vapor compression system which is able to operate as a water chiller and as a heat pump. The main aim of this study is to evaluate energy-saving potential of a scroll compressor at varying speed instead of classical thermostatic (on/off) control. The compressor speed was continuously controlled via fuzzy logic algorithm. For different working conditions, a significant energy saving on average equal to about 20% was obtained adopting a scroll compressor speed control algorithm, based on the fuzzy logic, in comparison with the classical thermostatic control.

In a different study by Aprea et al. [76], energy consumption of an electronic valve and a thermostatic expansion valve were compared in a cold store. The main aim of the study was to verify the best type of expansion valve for the energy point of view. The results showed that with a fuzzy algorithm, the thermostatic expansion valve allows an energy saving of about 8% in comparison with the electronic valve.

Heating, ventilating, and air-conditioning (HVAC) control application is also studied in control researches, broadly. Rahmati et al. [77] presented a new approach to control heating, ventilating, and air-conditioning (HVAC) system. The proposed method was a hybrid of fuzzy logic and PID controller. Fuzzy logic control showed better control performance than PID controller. According to Wang et al. [78], the controlled object in HVAC system has large inertia, pure lag, and nonlinear characteristic. Combined with the fuzzy control and general PID control, the temperature and humidity of the room were controlled in HVAC system of a TV building. The temperature of the studio was controlled through PID control, fuzzy control, and fuzzy-PID control. It was found that hybrid fuzzy-PID control has better adaptability and stability, less overshoot, faster response, and higher precision than PID control and fuzzy control. Navale [79] conducted experiments on two real HVAC systems to compare the performance of fuzz logic control and PID control. Results of this study showed that fuzzy control system required 0–185% more rise time, had 9–68% less overshoot, and required 11–45% less settling time as compared to the conventional PID-controlled system.

In a different study from the others, Li et al. [80] investigated a PID and a fuzzy logic control study for automobile air-conditioning system. In the study, improvement of the refrigerant flow control method by using an electronic expansion valve (EEV) was described. Also, the flow rate characteristic of the EEV for automobile air-conditioning was presented. A microcontroller was used to receive input signal and generate output signal to control the opening amount of the EEV. They employed a fuzzy self-tuning proportional-integralderivative (PID) control method. Experimental results showed that the new control method can feed adequate refrigerant flow into the evaporator in various operations. Also, evaporator discharge air temperature dropped by approximately 3°C as compared with the conventional PID control system.
