Rini Nur Hasanah

Alternative Grounding Method Using Coconut Shell Charcoal as Media of Mesh Electrodes

The utilization of coconut charcoal as alternative media of grounding was investigated. The mesh-electrode was made of stainless steel of 8-mm diameter, whereas its lattice dimension was 50cmx50cm. Four variations of lattice number were considered, i.e. 1-, 2-, and 4-lattice structures. Dry and wet charcoal media were considered. Mesh location was fixed in the depth of 80cm under the ground, while the 10cm of medium thickness variation was chosen. The resistance obtained using 10-cm thickness of charcoal layer in a mesh consisting of 1-, 2-, and 4-lattices were 268, 131, and 78 ohms consecutively. The addition of layer up to 80-cm resulted in a resistance decrease of 48%, 33%, and 44%. Using wet charcoal, the 10-cm layer produced 26.5, 17.5, and 14.8 ohms of grounding resistance and a reduction of 25%, 10%, and 3.6% subsequently for 1-, 2-, and 4-lattice mesh structure if the layer thickness was 80 cm.

Control of Pole-Climbing Robot Orientation using Self-Tuning Method

This paper describes the method to control a hybrid robot whose main task is to climb a pole to place an object on the top of the pole. The hybrid pole-climbing robot considered in this paper uses 2 Planetary PG36 DC-motors as actuators and an external rotary encoder sensor to provide a feedback on the change in robot orientation during the climbing movement. The orientation control of the pole-climbing robot using self-tuning method has been realized by identifying the transfer function of the actuator system under consideration, being followed with the calculation of control parameters using the self-tuning pole-placement method, and furthermore being implemented on the external rotary encoder sensor. Self-tuning pole-placement method has been explored to control the parameters q 0 , q 1 , q 2 , and p 1 of the controller. The experiments were done on a movement path in a form of a cylindrical pole. The first experiment was done based one the change in rotation angle of the rotary sensor with the angle values greater than 50˚ in the positive direction, whereas the second experiment was done with the angle values greater than -50˚ in the negative direction. The experiment results show that the control of the robot under consideration could maintain its original position at the time of angle change disturbance and that the robot could climb in a straight direction within the specified tolerance of orientation angle change.

LED-Lamp Design for Renewable Energy-Based DC House Application

This paper describes the method to control a hybrid robot whose main task is to climb a pole to place an object on the top of the pole. The hybrid pole-climbing robot considered in this paper uses 2 Planetary PG36 DC-motors as actuators and an external rotary encoder sensor to provide a feedback on the change in robot orientation during the climbing movement. The orientation control of the pole-climbing robot using self-tuning method has been realized by identifying the transfer function of the actuator system under consideration, being followed with the calculation of control parameters using the self-tuning pole-placement method, and furthermore being implemented on the external rotary encoder sensor. Self-tuning pole-placement method has been explored to control the parameters q 0 , q 1 , q 2 , and p 1 of the controller. The experiments were done on a movement path in a form of a cylindrical pole. The first experiment was done based one the change in rotation angle of the rotary sensor with the angle values greater than 50˚ in the positive direction, whereas the second experiment was done with the angle values greater than -50˚ in the negative direction. The experiment results show that the control of the robot under consideration could maintain its original position at the time of angle change disturbance and that the robot could climb in a straight direction within the specified tolerance of orientation angle change.

A Micro-Scale Cyclone-Wind Turbine for Rooftop Ventilator

Received Mar 3, 2018 Revised Apr 11, 2018 Accepted Apr 21, 2018 Paintball has gained a huge popularity in Malaysia with growing number of tournaments organized nationwide. Currently, Ideal Pro Event, one of the paintball organizer found difficulties to pair a suitable opponent to against one another in a tournament. This is largely due to the manual matchmaking method that only randomly matches one team with another. Consequently, it is crucial to ensure a balanced tournament bracket where eventual winners and losers not facing one another in the very first round. This study proposes an intelligent matchmaking using Particle Swarm Optimization (PSO) and tournament management system for paintball organizers. PSO is a swarm intelligence algorithm that optimizes problems by gradually improving its current solutions, therefore countenancing the tournament bracket to be continually improved until the best is produced. Indirectly, through the development of the system, it is consider as an intelligence business idea since it able to save time and enhance the company productivity. This algorithm has been tested using 3 size of population; 100, 1000 and 10,000. As a result, the speed of convergence is consistent and has not been affected through big population.N. N. S. Abdul Rahman, N.M. Saad, A. R. Abdullah, M. R. M. Hassan, M. S. S. M. Basir, N. S. M. Noor 1,2,4,6Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia 2,3Center for Robotics and Industrial Automation, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia 3,5Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MalaysiaLight rail transit (LRT), or fast tram is urban public transport using rolling stock similar to a tramway, but operating at a higher capacity, and often on an exclusive right-of-way. Indonesia as one of developing countries has been developed the LRT in two cities of Indonesia, Palembang and Jakarta. There are opinions toward the development of LRT, negative and positive opinions. To reveal the level of LRT development acceptance, this research uses machine learning approach to analyze the data which is gathered through social media. By conducting this paper, the data is modeled and classified in order to analyze the social sentiment towards the LRT development.Mohamad, S., Nasir, F.M., Sunar, M.S., Isa, K., Hanifa, R.M., Shah, S.M., Ribuan, M.N., Ahmad, A. 1,4,6,7,8Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 1,2,3UTM-IRDA Digital Media Centre, Media and Game Innovation Centre of Excellence, Universiti Teknologi Malaysia, Johor, Malaysia 1,2,3Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia 5Centre for Diploma Studies, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 6Research Centre for Applied Electromagnetics, Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaReceived Jan 31, 2018 Revised Apr 21, 2018 Accepted Apr 30, 2018 Bluetooth is an emerging mobile ad-hoc network that accredits wireless communication to connect various short range devices. A single hop network called piconet is the basic communication topology of bluetooth which allows only eight active devices for communication among them seven are active slaves controlled by one master. Multiple piconets are interconnected through a common node, known as Relay, to form a massive network called as Scatternet. It is obvious that the performance of Scatternet scheduling is highly dependent and directly proportionate with the performance of the Relay node. In contrary, by reducing the number of Relays, it may lead to poor performance, since every Relay has to perform and support several piconet connections. The primary focus of this study is to observe the performance metrics that affects the inter-piconet scheduling since the Relay node’s role is like switch between multiple piconets. In this paper, we address and analyze the performance issues to be taken into consideration for efficient data flow in Scatternet based on Relay node.

Prediction of Solar Radiation Intensity using Extreme Learning Machine

Applied Computing Technology (ACT), Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat, 86400 Johor, Malaysia. Department of Management Information Systems, College of Commerce and Business Administrations, Dhofar University, Salalah, Oman.

Design and construction of a single-arm crane miniature for stevedoring

This paper presents the design and construction of a single-arm crane in a reduced form, as an instructive model to understand its working and control principles. The model uses an arm length of 70 cm, representing a reduction scale of 1:100 of its actual size. The assigned maximum load was 2.5 kg, considering the availability of mechanical structure materials. A separately excited direct-current motor was chosen based on the requirements of load-torque characteristics and considering its ease of control and availability. The designed miniature crane uses 3 motors of 20.844W, 11.256W, and 10.81W to manoeuver the crane, i.e. to drive the boom, to tow the rope, and to rotate the crane respectively. The motors were driven using a MOSFET converter, whereas its trigger control was facilitated using a microcontroller. The experiment results indicated the ability of the crane miniature to move the load as previously determined in the specifications.

Single-Loop Optimization for Losses Minimization in Medium-Voltage Power Distribution System

One important goal during the reconfiguration of a medium-voltage power distribution network is to minimize the active-power losses of the system. Therefore, the objective function of an optimization problem would represent the total power losses of the distribution system, by considering only the active component of power losses while ignoring the reactive part. Constraints would be load flow, voltage drop, and the network configuration. In this paper, losses problem during the reconfiguration of a medium-voltage power distribution system have been minimized using a single-loop optimization method, whereas the load-flow analysis has been performed by utilizing the Newton-Raphson method. The optimization method was aimed to minimize the active-power losses of the system by formulating the problem as a matter of network reconfiguration. The solution scheme has been begun with a mesh distribution-network which had been obtained previously by assuming all the switches to be closed and then opened sequentially to eliminate loops. The optimization results showed that in a 21-bus distribution system there had been 10800 combinations, in which the lowest power losses occurred under the combination of NO 23, NO 21, NO 22, NO 24, NO 25, whereas the combination of NO 7, NO 10, NO 20, NO 15, NO 20, resulted in the power losses of 0.1676 per unit, being equal to 16.76 kVA at the base power of 100 kVA.

Optimization of the reactive power injection to control voltage profile by using artificial bee colony algorithm

The increasing demand for electric power requires the power system utility to continuously adapt the network system, both on the transmission line and the distribution systems. It may cause a voltage drop and other impact related to power losses because of the limited availability of reactive power source in the system. Therefore, implementation of compensation devices such as capacitor bank, Static VAR Compensator (SVC), and other Flexible AC Transmission System (FACTS) devices to inject reactive power to the network are needed. The optimum location and size of the compensation device must be determined appropriately. This paper presents two optimization approaches, including both deterministic and nondeterministic methods. Artificial bee colony (ABC) algorithm is applied to acquire the most optimum size and location of SVC. It is an optimization method using metaheuristic techniques which have been developed based on the intelligent behavior of honey bee. The IEEE standard 30-bus system data has been used to determine the performance of the ABC algorithm to control the voltage profile and power losses. Comparison of the voltage profile and power losses without and with an injection of SVC of the power system has been determined by using the ABC algorithm optimization method. Based on the analysis results, it was known that the SVC optimization could boost the voltage profile at all buses under consideration to the value higher than its minimum allowed voltage. Besides, the power losses condition has also been improved, with 35.36% active power improvement and 40.90% reactive power improvement subsequently.

Loading Performances of Low-Power Low-Speed Single-Phase Induction Generator with Energy Saving Lamps

The increasing use of energy saving lamps provides additional benefits to the application of low-power low-speed self-excited induction generators resulted from capacitor motor modification. Reactive power requirement of the generator can be provided from the capacitive nature of the lamps, while at the same time it is delivering active power to loads. Any loading change will automatically increase or reduce reactive power supply to generator. Results of experiments show that low-power low-speed single-phase self-excited induction generator is more robust and suitable for this kind of loads. Generator does not lose its voltage when experiencing abrupt change of loads. This robustness makes the generator suitable for the use in low-capacity hydropower generation in remote areas being commonly not covered by national electricity grid.

Optimization of Sun-Tracker Positioning Using Takagi-Sugeno Fuzzy-Logic Method

The continuously increasing use of photovoltaic cells requires various efforts to maximize the harnessing of solar energy. This paper presents the research results of fuzzy-logic method implementation to maximize the absorption of solar energy. It is based on the optimization of solar panels position according to the sun direction. The Takagi-Sugeno method is chosen in the fuzzification stage. The control algorithm is implemented on a microcontroller ATMega-128 using BASCOM-AVR program. DC motor is used to actuate the solar panels. The results show an increase of 0.48V in the output of solar cells sensor using the fuzzy logic computation-based tracking system. The resulted tracking system proves to consume less power because the tracking process is halted while moving the DC motor continuously.