Wafa Batayneh

Using a fuzzy Poka-Yoke based controller to restrain emissions in naturally ventilated environments

Gas poisoning as a result of fuel-burning inside confined environments claims the lives of many people worldwide. Gas poisoning treatment consists of administering oxygen therapy ranging from access to fresh air to breathing 100% oxygen by a tight fitting oxygen mask. Building on these facts, this article uses Poka-Yoke concepts to prevent, alert, and control the quality of air in naturally ventilated environments. The proposed controller ensures the access of victims to fresh air until help arrives. We target naturally ventilated indoor environments where no other ventilation approaches are installed. The proposed system utilizes fuzzy logic to control the speed and cycle time of two DC-motor-powered fans based on the levels of the oxides sensed by gas detectors. As a result, fresh air is allowed into the environment to replace the polluted air utilizing one fan set while hunted air is exhausted to the outdoors using the second fan set. The proposed system is simulated where obtained results for various scenarios confirm the many advantages of the system over natural ventilation.

Microscale Falling Cylinder Viscometer With Slip Boundary

This paper theoretically investigates the hydrodynamic behavior of a falling microcylinder viscometer. The Navier slip conditions are applied to all fluid/solid interfacial boundary conditions of the device. Previous investigations focused on the behavior at the macroscale level and did not consider the slip conditions. The slip coefficients for typical devices and operatireg conditions are found to be major parameters that affect the behavior of the microscale viscometer. Formulas for determining the viscosity coefficients using a microscale viscometer without considering slip conditions give inaccurate results. The theoretical model has been verified by comparing its predictions with that of the macroviscometer after neglecting the slip conditions.

Comparative Study of DC Motor Speed Control Using Neural Networks and Fuzzy Logic Controller

This paper demonstrates the importance of the intelligent controllers over the conventional methods. A speed control of the DC motor is developed using both Neural Networks and Fuzzy logic controller in MATLAB environment as intelligent controllers. In addition a conventional PID controller is developed for comparison purposes. Both intelligent controllers are designed based on the simulation results of the nonlinear equations in addition to the expert pre knowledge of the system. The output response of the system is obtained using the two types of the intelligent controllers, in addition to the conventional PID controller. The performance of the designed Neural Networks, Fuzzy logic controller and the PID controller is compared and investigated. Finally, the results show that the neural network has minimum overshoot, and minimum steady state parameters. This shows more efficiency of the intelligent controllers over the conventional PID controller. Also it shows that Neural Networks is better than Fuzzy logic controller in terms of over shoot and rising time. At the end of this paper an implementation of Graphical User Interface (GUI) method is developed. The main purpose of the GUI is to give the users a chance to use the program in a simple way without the need to understand the program languages.Copyright

Bluetooth Based Stair Climbing Robot Control Using Cell Phone

In this paper a tracked stair climbing robot will be developed. The robot can be controlled using any smart cell phone through Bluetooth. When designing the robot, the main constraints taken into consideration are the ability to climb the stairs in addition to the optimal size and weight; the robot needs to be small and light enough to get into places inaccessible by human. It needs also to be large enough to climb obstacles commonly found in any areas, such as rough terrains and stairs. Finally, it will be equipped with digital humidity and temperature sensor (DHT). A prototype of the stair climbing robot is designed and implemented, this robot is capable of moving on rough terrains and climbing a stair, it is portable due to the light material used in manufacturing. This robot will be controlled using two modes; the first one will use Arduino communicating by Bluetooth Module that can be connected with any smart mobile phone. The second mode (autonomous) will use the feedback from an ultrasonic sensor installed at the top of the robot and is able to rotate using a servo motor. The prototype is tested on different rough and inclined terrains, on grassy ground and on stairs. The overall system works successfully and it performs very well. Video of the working prototype is provided.Copyright

Fuzzy-GA inference technique to control three-input jet ejector system

Jet ejectors find many applications in thermal systems including refrigeration, heat treatment, and fuel injection. In this study, a three-input jet ejector model is developed and the resulting non-linear governing equations are used to design the corresponding controller. A fuzzy-based genetic algorithm (fuzzy-GA) technique is used to represent and control the system using linguistic fuzzy sets, which are tuned using a genetic algorithm code. The proposed controller is tested on different fluid types where simulation results showed the effectiveness and robustness of the technique.

Efficient approximation of melting temperature in simulated annealing algorithms applied to Chebyshev travelling salesman problem

Simulated annealing algorithms are widely used for solving NP-hard combinatorial optimisation problems including the travelling salesman problem (TSP). This article presents results of an empirical investigation for estimating the melting temperature for the simulated annealing algorithm based on the objective function value. We limit our search to Chebyshev order-picking systems with unequal horizontal and vertical speeds. The article utilises 90 randomly generated order-picking problems with densities ranging from 10 to 800 stops per tour. For each investigated problem, we utilise different seed values to generate and to solve ten replicates of the problem. Results show that quality melting temperature values can be estimated based on the statistical characteristics of the search space. This study helps to arrive at quality solutions with significantly fewer re-evaluations of the objective function.