The reliability of water supply system is a critical factor in the development and the ongoing capability to succeed in life and people's health. Determining of its, with high certainty, for performance of water supply system is developed to ensure the sustainability of system. Reliability (Re) plays a great role in evaluation of system sustainability. The probability approaches have been used to evaluate the reliability problems of systems. The probability approach is failed to address the problems of reliability evaluation that comes by subjectivity, human inputs and lack of history data. This research proposed two models; I) traditional model: fuzzy reliability measure suggested by Duckstein and Shresthaand then developed by El-Baroudy; and II) developed model: fuzzy reliability-vulnerability model. The two models implemented and evaluation of water supply system by using two hypothetical systems (G and H). System (G) consists of a single pump and System (H) consists of a two parallel pumps. Triangular and trapezoidal membership functions (MFs) are used to investigate of the reliability measure to the form of the membership function. The results agree with expectations that the reliability of parallel component system {ReH (0.53)} is higher than the reliability of single component system {ReG (0.47)}. Moreover, the result by using fuzzy set reduces the effect of subjectively in process of decision-making (DM). The fuzzy reliability vulnerability is able to handle different fuzzy representations and different operation environment of system
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
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.
Particle Swarm Optimization Algorithm (PSOA) has emerged recently as an efficient and powerful technique for the optimization of real parameters. The current study presents control scheme for electro-hydraulic actuator system which utilizes particle swarm optimization (PSO) for off-line tuning of the Fuzzy Proportional-Derivative (Fuzzy PD) controller. The gains and Membership Functions (MFs) tuned by PSOA which has been implemented depending on the performance indices: ITAE (Integral Time of Absolute Error), ISE (Integral Square of Error), and IAE (Integral Absolute of Error).
In this research a simply supported beam is used as a master structure with unknown number of attachments (fuzzy substructure) which is modeled as a system of 1-DOF attachments. Two types of attachments models were studied, namely 1-DOF mass attachment model and 1-DOF mass-spring attachment model. It is shown that the effect of attachments on the master structure natural frequencies when modeled as (mass-spring substructure) is larger than that when modeled as (mass substructure) for the same attachment mass. Engineering Statistics and normal distribution were used to find the values of the attachments to be added to the simply supported beam to improve the dynamical properties of the master structure and to find the best distribution of the attachment. The results also show that the distribution of the additional substructure can produce a great change in the natural frequencies so that the proposed statistical approach can be used to find the best distribution of attachments and number, value and location of the additional substructure .
This research provides a comparison between the performances of Sugeno type versus Mamdani-type fuzzy inference systems. The main motivation behind this research was to assess which approach provides the best performance for satellite image classification. The performance of each approach has been evaluated for six bands (from Landsat-5) for West Iraq image classification and compared with traditional method (Maximum likelihood), based on pixel-by-pixel technique. Due to the importance of performance in online systems we compare the Mamdani model, used previously, with a Sugeno formulation using four types of membership function (MF) generation methods. The first method triangular membership function using the mean, minimum and maximum of the histogram attribute values. The second approach generates triangular membership function using the peak and the standard deviation of attributes values. The third procedure generates Gaussian membership function using the mean and the standard deviation of the histogram attributes values. The fourth approach generates Gaussian membership function using the peak and the standard deviation of the histogram attributes values. The results show that the Mamdani models perform better in most of the case under study.