Reducing energy consumption and to ensure thermal comfort are two important considerations in designing an air conditioning system. The control strategy proposed is fuzzy logic controller (FLC).This paper describes the development of an algorithm for air condition control system based on fuzzy logic (FL) to provide the conditions necessary for comfort living inside a building.Simulation of the controlling air conditioning system, on which the strategy is adopted, was carried out based on MATLAB This system consists of two sensors for feedback control: one to monitor temperature and another one to monitor humidity. The controller i.e. FLC was developed to control the compressor motor speed and fan speed in order to maintain the room temperature at or close to the setpoint temperature.
In this work, a Fuzzy Model Reference Adaptive Controller FMRAC is presented for the speed control problem of a DC motor. The proposed controller is designed in two phases. In the first phase, the model reference input-output data is used to obtain the fuzzy rules. Then the effective rules are chosen to be used in the second phase. In the second phase, the obtained controller is applied in two conditions; the non fuzzy rules or adjusting the center of output membership functions. The simulation results shows a good speed motor tracking to the model reference in the word of the step response coefficients.
A solar water heating system has been fabricated and tested to analyze the thermal performance of Parabolic Trough Solar Collector (PTSC) using twisted tape insert inside absorber tube with twisted ratio about TR=y/w=1.33. The performance of PTSC system was evaluated by using three main important indicators: water outlet temperature (Tout), useful energy and thermal efficiency (ηth) under the effect of mass flow rate (ṁ) ranges between 0.02 and 0.04 Kg/s with the corresponding of Reynolds number (Re) range (2000 to 4000). In a parallel, a fuzzy-logic model was proposed to predict the thermal efficiency (ηth) and Nusselt number (Nu) of PTSC depending on the experimental results. The fuzzy model consists of five input and two output parameters. The input parameters include: solar intensity (I), receiver temperature (Tr), water inlet temperature (Tin), water outlet temperature (Tout) and water mass flow ( ) while, the output include the thermal efficiency (ηth) and Nu. The final results indicate that, owing to the mixture of the swirling flow of the perforated twisted-tape insert, the perforated twist tape insert enhances the heat transfer characteristics and the thermal efficiency of the PTSC system. More specifically, the use of perforate twist tape inserts enhanced the thermal efficiency by 4% to 4.5% higher than smooth absorber tube. Also, the predicted values were found to be in close agreement with the experimental counterparts with accuracy of ~92 %. So, the suggested Fuzzy model system would have high validity and precision in forecasting the success of a PTSC system compared to that of the traditional model. Pace, versatility, and the use of expert knowledge for estimation relative to those of the traditional model are the advantages of this approach