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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,174 Documents
 702   703   704   705   706 
Full state feedback and feed forward control of servo smart window using MATLAB/Simulink Rany Ayu Lestari; Unan Yusmaniar Oktiawati
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1355-1362

Abstract

House as a place to carry out daily activities requires healthy air. The right step to improve air circulation is to use smart window. A control system method is needed so that smart windows can automate air circulation better. Temperature sensor will determine the minimum, maximum, and opening size of the smart window in order to perform the function of opening and closing effectively. Servo motors are used as actuators in the process of opening - closing windows. In this research, the full state feedback and feed forward control method are used to determine the best control theory for servo motor control for smart window systems. The motor control system modeling in smart window is designed by applying the previously studied control theory. Mathematical modeling was carried out to obtain system equations and performance index. The equation is then applied to the MATLAB/Simulink simulation so that the stability of the system can be monitored against disturbances in the form of noise originating from the sensor or the control system itself.
Automated drainage system for thermoelectric power plant Max Melgarejo-Jara; Omar Chamorro-Atalaya; Florcita Aldana-Trejo; Nestor Alvarado-Bravo; José Farfán-Aguilar; Erika Zevallos-Vera; Evelyn Anicama-Navarrete
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1393-1401

Abstract

The Chilca 2 thermoelectric power plant, located in the province of Lima, Peru, has an open cycle gas turbine and a combined cycle steam turbine, whose combined capacity is 112.8 MW (Mega Watts). This plant requires auxiliary equipment for its operation, which is why it consists of electrical systems, lubrication system, hydraulic ventilation, pumps, vacuum systems and drainage of condensate generated by the difference in temperature in the steam conductor. Said drainage system is inside a 5-meter-deep basement that, being exposed to the elements, is exposed to falling drops of water that are generated by the vapors that are released due to the difference in temperature, repeatedly flooding and exposing to hazards that affect the normal operation of the thermoelectric plant. The proposed solution is based on the philosophy of a feedback control system, which uses a programmable logic controller (PLC) Siemens 1214AC/DC/Relay programmable logic controller, which, through a frequency inverter, activates the drainage pumps; the frequency range at which the variator works is linked to a 4-position level sensor. The result shows that it was possible to activate the frequency variator in a controlled manner through frequencies of 10 Hz, 30 Hz and 60 Hz, in this way a sustained operation of the drainage system is guaranteed.
Correlation based data unification for personality trait prediction Radha Divi; Chandra Sekhar Potala
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp404-411

Abstract

The data points created by users with their online behavior are the primary source of data analysis in various research studies. One of such studies that even more contributes directly or indirectly to other application domains is personality trait analysis. There are well-defined models witnessed to be strong enough to characterize the individual personalities. Some prominent models are the Big Five, Interpersonal Circumplex, and DISC. To make it possible the model should always be fed with a huge amount of data. Here comes the limitation is that the user's online behavior is spread across various platforms resulting in various forms of data points. The segregated form of the data limits the model performance, which is the primary focus of the proposed work. Among these, the big five personality traits model has become so familiar because of its simplicity and dominance. The proposed work illustrated the mapping of various data forms namely measures of the source dataset (MBTI) and Interpersonal Circumplex data to Big five data.
Cocktail parity problem solution based on modified blind extraction technique Ahmed Kareem Abdullah; Hadi A. Hamed; Ali A. Abdullah Albakry; Ahmed Ghanim Wadday
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp793-800

Abstract

The Cocktail Party Problem solution is described as being the responsibility of isolating the voice signal in a noisy environment. Two popular methods for resolving this issue are blind source extraction and the Wiener filtering procedure. The blind source extraction approaches like fastICA, JADE and efficient fastICA are useful for extraction data from the mixed signals. The classical optimization techniques such as genetic algorithms or particle swarms for blind source extraction are mostly founded on the gradient and need the objective function, so the using of these techniques is very restricted. In the recent studies, the classical blind source separation techniques will not give the perfect solution for the cocktail parity problem. These methods struggle with convergence speed and accuracy issues as well. In order to enhance the separation process and get over these issues, this work adopted the glowworm swarm technique based on kurtosis as the objective function. The results show that the proposed technique produces good separation. The original and estimated signals are compared for similarity using the cross-correlation function.
Design and prototyping of an accelerometer based parallel manipulator for endoscope position control Kalyan Dusarlapudi; Kuthuri Narasimha Raju; Kolusu Kishore Kumar; Kattupalli Sudhakar; Charan Sai Tiruvuri
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1320-1329

Abstract

The advancement of embedded controllers in minimally invasive robotic surgery (MIRS) provides an innovative and safe alternative to traditional open surgery. This paper illustrates the Accelerometer-based Embedded prototype of 4 link novel parallel manipulator design and endoscope end position control scheme. The parallel manipulator proposed is of 4 leg quadra model with 4 servo actuators to drive the end effector to which endoscope camera integrated with micro electro-mechanical system (MEMS) accelerometer. The parallel manipulator is modeled in Coppeliasim computer-aided design (CAD) and embedded control logic is implemented in the ATmega328P microcontroller. The achieved end effector movement is +/-10cm from the ground clearance validated it in CAD tool. The potentiometer-based position control of the endoscope and its image magnification is recorded. The internet of things (IoT) infrastructure extension to the demonstrated protype is proposed. This cost-effective model is compared with the existed models available in the market.
Internet of things based real-time electric vehicle and charging stations monitoring system Emad A. Mohammed; Mahmood Hameed Qahtan; Ahmed J. Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1661-1669

Abstract

Due to a shortage of fuel sources and the increment in environmental pollution, efficient techniques should be introduced. The best solution is to move to the use of electric vehicles. The article aims to develop a solution for electric vehicle (EV) charging station locations that utilize the internet of things (IoT) technology. The IoT is a paradigm that uses sensors and transmitting networks to provide current facilities with a real-time global communication perspective of the physical world. This paper proposes a real-time system to provide a real-time update to EV location and charging stations (CSs) location to reduce time lost by users searching CSs, and provides real-time charging station (CS) recommendations for EV users by displaying the nearest CS, provide estimation arrival time to the nearest CS, display distance between nearest CS and EV real-time updated. The work of the proposed system was tested, and the most significant error rate (17 meters) is represented by the difference in the distance obtained from the system and the distance obtained from Google Map. The total accuracy of the design for the tested case is (98.014%).
Optimization of location and rating of unified power flow controllers for congestion management Vengadesan Alagapuri; Ashok Bakkiyaraj Radhakrishnan; Sakthivel Sithangkathan; Jayanthi Kalikrishnan
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1258-1267

Abstract

Large number of contracted power exchanges among sellers and purchasers, in a deregulated power market causes transmission line congestion. Congestion of lines undermines the security and economy of power networks. Flexible AC transmission system (FACTS) devices are introduced at appropriate spots to change the power flow in order to keep the flow of the lines within their capability. In this work, the most commonly used unified power flow controller (UPFC) is proposed for achievement of changing the line flow and for easing congestion from the over loaded lines. The size and site of UPFC controllers significantly impact their performance in congestion management task. The location and size of the UPFC devices are to be optimized by using an optimization algorithm. Whale optimization algorithm (WOA) is exploited in this effort for realizing the aim of determination of site and size of the FACTS converters. The present method has lesser quantity of variables which are tuned to get best outcomes. The suggested WOA based technique is executed on the IEEE 57 bus system. The outcomes comparison is made with particle swarm optimization algorithm (PSO) and firefly algorithm (FFA) and the better improved outcomes are found.
An investigation of machine learning techniques in speech emotion recognition Anu Saini; Amit Ramesh Khaparde; Sunita Kumari; Salim Shamsher; Jeevanandam Joteeswaran; Seifedine Kadry
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp875-882

Abstract

The natural languages are medium of communication from the inception of civilization. As the technology improves, the text messages, voice messages and videos are the addons in medium of communication. In long distance communication, the analysis of expression is modern area of research. The parameters of assessment are subjective hence the emotion recognition is challenging task. This article furnishes the investigation of various machine learning techniques and novel methods for speech emotion recognition (SER) to determine the feeling/sentiments in a speech. Here, we investigate the three machine learning methods named multinominal Naive Bayes (MNB), logistic regression (LR), and linear support vector machine (LSVM). Further, these techniques are incorporated with the proposed method. The performance of these machine learning techniques is investigated on two different datasets.  The datasets consist of voice and text data samples. The prosed method is trained and tested on these datasets. As per the experimentation, it has been observed that the LSVM has outperformed the other two machine learning techniques.
Determination of support vector regression parameters using African buffalo optimization algorithm Inusa Sani Maijama’a; Yuhanis Yusof; Mohamad Farhan Mohsin
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp1088-1095

Abstract

The use of support vector regression (SVR) for regression tasks has been on increase over the past few years. Unfortunately, the practical application of SVR for regression task is limited due to its dependence on proper setting of its hyper-parameters and associated kernel parameter. Therefore, it become imperative to device a reliable and fast mechanism of determining the value of these parameters that could guarantee lowest generalization error. This paper presents SVR parameter optimization approaches using African buffalo optimisation (ABO) algorithm, i.e. SVR-ABO. The SVR parameters are optimized by using African buffalo optimisation algorithm. Results obtained from several experiments performed has shown that the proposed ABO algorithm has the capability of determining SVR hyper-parameters which most of time has to be done through estimation.
Diagnosis of induction motor failures using discrete wavelet transform of an auxiliary winding voltage Yakout Khadouj Jelbaoui; Lamiaa El Menzhi; Abdallah Saad
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1231-1241

Abstract

Over last years, great attention has been developed to avoid the machines breakdown especially in the squirrel cage induction motor which suffer from different failures. The aim of this paper is to present a new method for the diagnosis of rotor bar breakage and end ring in induction machine fed by an inverter based on discrete wavelet transform applied on the voltage of an auxiliary winding as a new monitoring signature. The expression of the auxiliary winding voltage related to a small coil inserted between two stator phases is presented. The study is focused on the high-level signals of approximation and details coefficients. Thus, the evolution of any frequency of interest in the waveform is given in this paper. The method is validated by simulations of four broken bars and end ring cases under unloaded and loaded machine.

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