Mohanad Alata

Bio: Mohanad Alata is an academic researcher from King Saud University. The author has contributed to research in topic(s): Fuzzy logic & Fuzzy control system. The author has an hindex of 9, co-authored 23 publication(s) receiving 369 citation(s). Previous affiliations of Mohanad Alata include Jordan University of Science and Technology & Concordia University.

Developing a multipurpose sun tracking system using fuzzy control

Abstract: The present work demonstrates the design and simulation of time controlled step sun tracking systems that include: one axis sun tracking with the tilted aperture equal to the latitude angle, equatorial two axis sun tracking and azimuth/elevation sun tracking. The first order Sugeno fuzzy inference system is utilized for modeling and controller design. In addition, an estimation of the insolation incident on a two axis sun tracking system is determined by fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm, along with least square estimation (LSE), generates the fuzzy rules that describe the relationship between the input/output data of solar angles that change with time. The fuzzy rules are tuned by an adaptive neuro-fuzzy inference system (ANFIS). Finally, an open loop control system is designed for each of the previous types of sun tracking systems. The results are shown using simulation and virtual reality. The site of application is chosen at Amman, Jordan (32° North, 36° East), and the period of controlling and simulating each type of tracking system is the year 2003.

Optimizing of Fuzzy C-Means Clustering Algorithm Using GA

Abstract: Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models. Keywords—Fuzzy clustering, Fuzzy C-Means, Genetic Algorithm, Sugeno fuzzy systems.

Transient behaviour of a thermoelectric device

Abstract: The objective of this work is to describe the dynamic thermal behaviour of thermoelectric generators and refrigerators. In practical situations, these devices work under transient operating conditions due to the time change in the imposed current, voltage, and hot or cold temperatures. Results for transient temperature distribution were obtained for different parameters. The coefficient of performance was obtained as a function of time for increasing current flow.

Transient Behavior of a Thermoelectric Device Under the Hyperbolic Heat Conduction Model

Abstract: The major objective of this work is to describe the dynamic thermal behavior of thermoelectric generators and refrigerators under the effect of the hyperbolic heat conduction model. In practical situations, these devices work under transient operating conditions due to the time change in the imposed current, voltage, and hot or cold temperatures. Results for transient temperature distributions were obtained for different parameters. The coefficient of performance was obtained as a function of time for increasing current flow.

Adaptive control of a class of nonlinear systems with a first-order parameterized Sugeno fuzzy approximator

Abstract: In this paper, an adaptive fuzzy control scheme for tracking a class of continuous-time plants is presented. A parameterized Sugeno fuzzy approximator is used to adaptively compensate for the plant nonlinearities. All parameters in the fuzzy approximator are tuned using a Lyapunov-based design. In the fuzzy approximator, first-order Sugeno consequents are used in the IF-THEN rules of the fuzzy system, which has a better approximation capability than those using constant consequents. Global boundedness of the adaptive system is established. Finally, a simulation is used to demonstrate the effectiveness of the proposed controller.

A review of principle and sun-tracking methods for maximizing solar systems output

Abstract: Finding energy sources to satisfy the world's growing demand is one of society's foremost challenges for the next half-century. The challenge in converting sunlight to electricity via photovoltaic solar cells is dramatically reducing $/watt of delivered solar electricity. In this context the sun trackers are such devices for efficiency improvement. The diurnal and seasonal movement of earth affects the radiation intensity on the solar systems. Sun-trackers move the solar systems to compensate for these motions, keeping the best orientation relative to the sun. Although using sun-tracker is not essential, its use can boost the collected energy 10–100% in different periods of time and geographical conditions. However, it is not recommended to use tracking system for small solar panels because of high energy losses in the driving systems. It is found that the power consumption by tracking device is 2–3% of the increased energy. In this paper different types of sun-tracking systems are reviewed and their cons and pros are discussed. The most efficient and popular sun-tracking device was found to be in the form of polar-axis and azimuth/elevation types.

Perspectives of fuzzy systems and control

Abstract: Although fuzzy control was initially introduced as a model-free control design method based on the knowledge of a human operator, current research is almost exclusively devoted to model-based fuzzy control methods that can guarantee stability and robustness of the closed-loop system. State-of-the-art techniques for identifying fuzzy models and designing model-based controllers are reviewed in this article. Attention is also paid to the role of fuzzy systems in higher levels of the control hierarchy, such as expert control, supervision and diagnostic systems. Open issues are highlighted and an attempt is made to give some directions for future research.

Applications of fuzzy logic in renewable energy systems – A review

Abstract: In recent years, with the advent of globalization, the world is witnessing a steep rise in its energy consumption. The world is transforming itself into an industrial and knowledge society from an agricultural one which in turn makes the growth, energy intensive resulting in emissions. Energy modeling and energy planning is vital for the future economic prosperity and environmental security. Soft computing techniques such as fuzzy logic, neural networks, genetic algorithms are being adopted in energy modeling to precisely map the energy systems. In this paper, an attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications. It is found that fuzzy based models are extensively used in recent years for site assessment, for installing of photovoltaic/wind farms, power point tracking in solar photovoltaic/wind, optimization among conflicting criteria. The review indicates that fuzzy based models provide realistic estimates.

Sun Tracking Systems: A Review

Abstract: The output power produced by high-concentration solar thermal and photovoltaic systems is directly related to the amount of solar energy acquired by the system, and it is therefore necessary to track the sun's position with a high degree of accuracy. Many systems have been proposed to facilitate this task over the past 20 years. Accordingly, this paper commences by providing a high level overview of the sun tracking system field and then describes some of the more significant proposals for closed-loop and open-loop types of sun tracking systems.

A multipurpose dual-axis solar tracker with two tracking strategies

Abstract: This paper deals with a multipurpose dual-axis solar tracker that can be applied to solar power systems. This tracker employs a declination-clock mounting system that locates the primary axis in east-west direction. Based on this mounting system, normal tracking strategy and daily adjustment strategy are developed for flat Photovoltaic (PV) systems and Concentrating Solar Power (CSP) systems respectively. While the former strategy keeps the tracking errors smaller than the pre-specified values, the latter one simplifies the tracking process by adjusting the primary axis once a day and driving the secondary axis to rotate at a constant speed of 15°/h. Results of the accuracy test indicate that the tracking error of the normal tracking strategy is within 0.15°. The other strategy may have greater tracking errors, but its annual average cosine loss for flat PV systems is estimated to be below 1.3%. Furthermore, in the test on the output of the PV modules, it is found that the average energy efficiency of the normal tracking PV, compared with the fixed PV, is more than 23.6%. And the average energy efficiency of the daily adjusted PV is more than 31.8%. Results of the experiment show that the two tracking strategies are both feasible for the developed tracker.