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Featured researches published by Sy Yi Sim.


Archive | 2014

Vector Control of Induction Motor Using Neural Network

Azuwien Aida Bohari; Wahyu Mulyo Utomo; Zainal Alam Haron; Nooradzianie Muhd. Zin; Sy Yi Sim; Roslina Mat Ariff

This paper deals with field oriented control of induction motor drive system with an online neural network for speed control. The field oriented control used to decoupling the flux and torque in order to get the performance as well as direct current motor. The online neural network is designed to maintain the output speed variation. To verify the effectiveness of the proposed method, a simulation model was developed. The result shows that the performance of transient response is improved in term of overshoot and settling time by using neural network field oriented control system. It is concluded that neural network based field oriented control schemes of induction motor drive is more effective to replace the conventional proportional integral derivative based field oriented control technique.


Archive | 2013

Induction Motor Drive Based Neural Network Direct Torque Control

Sy Yi Sim; Wahyu Mulyo Utomo; Zainal Alam Haron; Azuwien Aida Bohari; Nooradzianie Muhd. Zin; Roslina Mat Ariff

A neural network based direct torque control of an induction motor was presented in this paper. The paper trained a neural network for speed controller of the machine to use in the feed-back loop of the control system. The description of the control system, training procedure of the neural network is given in this paper. The complete neural network based direct torque control scheme of induction motor drive is simulated using MATLAB. The acquired results compared with the conventional direct torque control reveal the effectiveness of the neural network based direct torque control schemes of induction motor drives. The proposed scheme improved the performance of transient response by reduces the overshoot. The validity of the proposed method is verified by the simulation results.


Indonesian Journal of Electrical Engineering and Computer Science | 2018

Evolution of Precision Agriculture Computing towards Sustainable Oil Palm Industry

Kai Chen Goh; Sy Yi Sim; Hui Hwang Goh; K. Bilal; T.H. Sam; T.Y. Teoh; Jia Sin Tey

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.


Indonesian Journal of Electrical Engineering and Computer Science | 2018

The Study of Stresses on Soil From Roadways Using Plaxis To Generate Potential Energy With Piezoelectric

Alvin Lim; Sy Yi Sim; Nickholas Anting; Joewono Prasetijo; T. I. T Noor Hasanah; Hui Hwang Goh; Yonis. M. Buswig; C.C. Kang

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.


Indonesian Journal of Electrical Engineering and Computer Science | 2018

Enhance Cascaded H-Bridge Multilevel Inverter with Artificial Intelligence Control

Sy Yi Sim; C.K. Chia; Wahyu Mulyo Utomo; Hui Hwang Goh; Yonis. M. Buswig; A. J. M. S. Lim; Sie Long Kek; Azuwien Aida Bohari; Cham C.L

Received Dec 04, 2017 Revised Jan 11, 2018 Accepted Apr 15, 2018 Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.A Weblogs contains the history of User Navigation Pattern while user accessing the websites. The user navigation pattern can be analyzed based on the previous user navigation that is stored in weblog. The weblog comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The aim of the research is to identifying the interested user behavior and not interested user behavior based on classification. The process of identifying user interest, it consists of Modified Span Algorithm and Personalization Algorithm based on the classification algorithm user prediction can be analyzed. The research work explores to analyze user prediction behavior based on user personalization that is captured from weblogs.Wireless Body Area Networks (WBANs) are fundamental technology in health care that permits the information of a patient’s essential body parameters to be gathered by the sensors. However, the safety and concealment defense of the gathered information is a key uncertain problem. A Hybrid Key Management (HKM) scheme [13] is worked based on Public Key Cryptography (PKC)-authentication scheme. This scheme uses a oneway hash function to construct a Merkle Tree. The PKC method increase the computational complexity and lacking scalability. Additionally, it increases expensive computation, communication costs and delay. To overcome this problem, Robust Security for Protected Health Information by ECC with signature Hash Function in WBAN (RSP) is proposed. The system employs hash-chain based key signature technique to achieve efficient, secure transmission from sensor to user in WBAN. Moreover, Elliptical Curve Cryptography algorithm is used to verifies the authenticate sensor. In addition, it describes the experimental results of the proposed system demonstrate the efficient data communication in a network.


Advances in Pure Mathematics | 2018

Discrete-Time Nonlinear Stochastic Optimal Control Problem Based on Stochastic Approximation Approach

Sie Long Kek; Sy Yi Sim; Wah June Leong; Kok Lay Teo

In this paper, a computational approach is proposed for solving the discrete-time nonlinear optimal control problem, which is disturbed by a sequence of random noises. Because of the exact solution of such optimal control problem is impossible to be obtained, estimating the state dynamics is currently required. Here, it is assumed that the output can be measured from the real plant process. In our approach, the state mean propagation is applied in order to construct a linear model-based optimal control problem, where the model output is measureable. On this basis, an output error, which takes into account the differences between the real output and the model output, is defined. Then, this output error is minimized by applying the stochastic approximation approach. During the computation procedure, the stochastic gradient is established, so as the optimal solution of the model used can be updated iteratively. Once the convergence is achieved, the iterative solution approximates to the true optimal solution of the original optimal control problem, in spite of model-reality differences. For illustration, an example on a continuous stirred-tank reactor problem is studied, and the result obtained shows the applicability of the approach proposed. Hence, the efficiency of the approach proposed is highly recommended.


MATHEMATICAL METHODS AND COMPUTATIONAL TECHNIQUES IN SCIENCE AND ENGINEERING | 2017

Optimal control of a coupled tanks system with model-reality differences

Sy Yi Sim; Sie Long Kek; Kim Gaik Tay

In this paper, an efficient computational approach is proposed to optimize and control a coupled tanks system. Since the dynamics of the coupled tanks system is nonlinear, determination of the optimal water level in the tanks could be formulated as an optimal control problem for a useful operation decision. For simplicity, the linear model of the coupled tanks system is suggested to give the true operating height of the coupled tanks. In our approach, the adjustable parameter is added into the model used. The aim is to measure the differences between the real plant and the model used repeatedly during the computation procedure. In this way, the optimal solution of the model used can be updated iteratively. On this basis, system optimization and parameter estimation are integrated. At the end of the iteration procedure, the converged solution approximates to the correct optimal solution of the original optimal control problem, in spite of model-reality differences. For illustration, the numerical parameter...


2014 Electrical Power, Electronics, Communicatons, Control and Informatics Seminar (EECCIS) | 2014

Neural network SVPWM-DTC of induction motor for EV load model

Sy Yi Sim; Wahyu Mulyo Utomo; Zainal Alam Haron; Azuwien Aida Bohari; Nooradzianie Muhammad Zin; Roslina Mat Ariff

A three phases induction motor is used as an electric vehicle propulsion system in this paper. The proposed neural network speed controller is design based on the space vector modulation technique on direct torque control. Since the electric drive performance significantly lean against on the design of speed controller, thus the improvement on the speed controller become the core of this research and so it is enhanced by replace the generic speed controller by the adaptive neural network controller. The performance of the control system in addition with the neural network learning scheme are depict in this paper. The complete schemes of both conventional and proposed scheme are simulated using Mathlab. The comparison system performance between the conventional direct torque control and the proposed intelligent neural network speed control have been investigated and show a satisfy result in both steady state and transient response. The simulation results verify that the proposed direct torque controller with the adaptive speed controller for induction motor satisfy and effectiveness enough as the candidate for electric vehicle propulsion.


Archive | 2013

Speed Control of Permanent Magnet Synchronous Motor Using FOC Neural Network

Nooradzianie Muhd. Zin; Wahyu Mulyo Utomo; Zainal Alam Haron; Azuwien Aida Bohari; Sy Yi Sim; Roslina Mat Ariff

This paper presents the performance analysis of the field oriented control for a permanent magnet synchronous motor drive with a proportional-integral-derivative and artificial neural network controller in closed loop operation. The mathematical model of permanent magnet synchronous motor and artificial neural network algorithm is derived. While, the current controlled voltage source inverter feeding power to the motor is powered from space vector pulse width modulation current controlled converter. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-Simulink program. The simulation results prove the proposed artificial neural network controller produce significant improvement control performance compare to the proportional-integral-derivative controller for both condition controlling speed reference variations and constant load. It can conclude that by using proposed controller, the overshoot, steady state error and rise time can be reducing significantly.


Archive | 2013

Fuzzy Logic Control Design for Induction Motor Speed Control Improvement Through Field Oriented Control

Roslina Mat Ariff; Dirman Hanafi; Whayu Mulyo Utomo; Kok Boon Ching; Nooradzianie Muhammad Zin; Sy Yi Sim; Azuwien Aida Bhohari

This paper focuses on improving induction motor performance by controlling its speed. The induction motor speed is controlled using field oriented control based structure associated with an induction motor. The field oriented control is implemented by combining with fuzzy logic control to reduce the uncertainties factors. The fuzzy logic control is developed based on Mamdani method. The inputs of fuzzy logic control are the error and derivative error between actual and reference speed of induction motor. The output of fuzzy logic control is the reference electric torque. The fuzzy logic control input output variables membership functions are chosen based on the parameters of the motor model. Motor state variables are identified indirect from induction motor model. The controller develops is implemented MATLAB Simulink. The simulation result shows that the fuzzy logic control is a suitable controller for improving induction motor performance with gives less settling time and steady state error than Proportional Integral Derivative control.

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Azuwien Aida Bohari

Universiti Tun Hussein Onn Malaysia

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Wahyu Mulyo Utomo

Universiti Tun Hussein Onn Malaysia

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Roslina Mat Ariff

Universiti Tun Hussein Onn Malaysia

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Nooradzianie Muhammad Zin

Universiti Tun Hussein Onn Malaysia

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Zainal Alam Haron

Universiti Tun Hussein Onn Malaysia

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Hui Hwang Goh

Universiti Tun Hussein Onn Malaysia

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Sie Long Kek

Universiti Tun Hussein Onn Malaysia

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Dirman Hanafi

Universiti Tun Hussein Onn Malaysia

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Nooradzianie Muhd. Zin

Universiti Tun Hussein Onn Malaysia

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Yonis. M. Buswig

Universiti Malaysia Sarawak

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