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27,762 Article Results

Finite-Control-Set Predictive Current Control Based Real and Reactive Power Control of Grid-Connected Hybrid Modular Multilevel Converter

10.11591/ijpeds.v9.i2.pp660-667
Rashmi Ranjan Behera , Amarnath Thakur
This paper proposes the grid application of modified three-phase topology of Modular Multilevel Converter (MMC) using finite-control-set predictive control. This topology has reduced number of switch counts compared to the conventional MMC, eliminates the problem of circulating current and having higher efficiency. A single dc source is required to produce sinusoidal outputs. The number of sub-modules (SMs) in this topology is half of the SMs required in case of MMC, in addition to a single H-bride circuit per phase. The finite-control-set predictive current control scheme for the grid connected dc source through the Hybrid Modular Multilevel Converter (HMMC). This controller controls the desired real and reactive power demand of the grid instantaneously. The simulation study of a three phase grid connected system has been done in Matlab/Simulink and the results are provided for the different real and reactive power demands, to validate the concepts.
Volume: 9
Issue: 2
Page: 660-667
Publish at: 2018-06-01

Nonlinear Adaptive Control for Wind Turbine Under Wind Speed Variation

10.11591/ijra.v7i2.pp87-95
Abdelhaq.Amar bensaber , Mustapha Benghanem , Mohammed.Amar bensaber , Abdelmadjid. Guerouad
Wind turbines components work as nonlinear systems where electromechanical parameters change frequently [1], which makes nonlinear control an interesting solution to prevail good efficiency. SMC has been largely used in electrical power applications because it offers interesting features like robustness to parametric uncertainties and external disturbances, to conquer the biggest drawback of the SMC, adaptation strategy consists on updating the sliding gain and the turbine torque to contribute with some important characteristics such as chatter-free performance, heftiness, robustness and secure power system operation. Matlab tests are introduced and compared.
Volume: 7
Issue: 2
Page: 87-95
Publish at: 2018-06-01

Grid and Force Based Sensor Deployment Methods in Wireless Sensor Network using Particle Swarm Optimization

10.11591/ijeecs.v10.i3.pp1287-1295
Aparna Pradeep Laturkar , Sridharan Bhavani , DeepaliParag Adhyapak
Wireless Sensor Network (WSN) is emergingtechnology and has wide range of applications, such as environment monitoring, industrial automation and numerous military applications. Hence, WSN is popular among researchers. WSN has several constraints such as restricted sensing range, communication range and limited battery capacity. These limitations bring issues such as coverage, connectivity, network lifetime and scheduling & data aggregation. There are mainly three strategies for solving coverage problems namely; force, grid and computational geometry based. PSO is a multidimensional optimization method inspired from the social behavior of birds called flocking. Basic version of PSO has the drawback of sometimes getting trapped in local optima as particles learn from each other and past solutions. This issue is solved by discrete version of PSO known as Modified Discrete Binary PSO (MDBPSO) as it uses probabilistic approach. This paper discusses performance analysis of random; grid based MDBPSO (Modified Discrete Binary Particle Swarm Optimization), Force Based VFCPSO and Combination of Grid & Force Based sensor deployment algorithms based on interval and packet size. From the results of Combination of Grid & Force Based sensor deployment algorithm, it can be concluded that its performance is best for all parameters as compared to rest of the three methods when interval and packet size is varied.
Volume: 10
Issue: 3
Page: 1287-1295
Publish at: 2018-06-01

Design of Robust Fractional-Order PID Controller for DC Motor Using the Adjustable Performance Weights in the Weighted-Mixed Sensitivity Problem

10.11591/ijra.v7i2.pp108-118
Toufik Amieur , Moussa Sedraoui , Oualid Amieur
This paper deals with the robust series and parallel fractional-order PID synthesis controllers with the automatic selection of the adjustable performance weights, which are given in the weighted-mixed sensitivity problem. The significant contribution of the paper is to achieve the good trade-off between nominal performances and robust stability for DC motor regardless its nonlinear dynamic behavior, the unstructured model uncertainties and the effect of the sensor noises on the feedback control system. The main goal is formulated as the weighted-mixed sensitivity problem with unknown adjustable performance weight.  This problem is then solved using an adequate optimization algorithm and its optimal solution leads to determine simultaneously the robust fractional PID controller, which is proposed by the series and the parallel fractional structures, As well as, the obtained optimal solution determines the corresponding adjustable performance weight. The proposed control technique is applied on DC motor where its dynamic behavior is modeled by unstructured multiplicative model uncertainty. The obtained performances are compared in frequency- and time-domains with those given by both integer controllers such classical PID and H∞ controllers.
Volume: 7
Issue: 2
Page: 108-118
Publish at: 2018-06-01

Exponential Reaching Law and Sensorless DTC IM Control with Neural Network Online Parameters Estimation based on MRAS

10.11591/ijra.v7i2.pp77-86
Legrioui Said , Rezgui Salah Eddine , Benalla Hocine
The most important problem in the control of induction machine (IM) is the change of its parameters, especially the stator resistance and rotor-time constant. The objective of this paper is to implement a new strategy in sensorless direct torque control (DTC) of an IM drive. The rotor flux based model reference adaptive system (MRAS) is used to estimate conjointly the rotor speed, the stator resistance and the inverse rotor time constant, the process of the estimation is performed on-line by a new MRAS-based artificial neural network (ANN) technique. Furthermore, the drive is complemented with a new exponential reaching law (ERL), based on the sliding mode control (SMC) to significantly improve the performances of the system control compared to the conventional SMC which is known to be susceptible to the annoying chattering phenomenon. An experimental investigation was carried out via the Matlab/Simulink with real time interface (RTI) and dSPACE (DS1104) board where the behavior of the proposed method was tested at different points of IM operation.
Volume: 7
Issue: 2
Page: 77-86
Publish at: 2018-06-01

A Survey on Cleaning Dirty Data Using Machine Learning Paradigm for Big Data Analytics

10.11591/ijeecs.v10.i3.pp1234-1243
Jesmeen M. Z. H , J. Hossen , S. Sayeed , CK Ho , Tawsif K , Armanur Rahman , E.M.H. Arif
Recently Big Data has become one of the important new factors in the business field. This needs to have strategies to manage large volumes of structured, unstructured and semi-structured data. It’s challenging to analyze such large scale of data to extract data meaning and handling uncertain outcomes. Almost all big data sets are dirty, i.e. the set may contain inaccuracies, missing data, miscoding and other issues that influence the strength of big data analytics. One of the biggest challenges in big data analytics is to discover and repair dirty data; failure to do this can lead to inaccurate analytics and unpredictable conclusions. Data cleaning is an essential part of managing and analyzing data. In this survey paper, data quality troubles which may occur in big data processing to understand clearly why an organization requires data cleaning are examined, followed by data quality criteria (dimensions used to indicate data quality). Then, cleaning tools available in market are summarized. Also challenges faced in cleaning big data due to nature of data are discussed. Machine learning algorithms can be used to analyze data and make predictions and finally clean data automatically.
Volume: 10
Issue: 3
Page: 1234-1243
Publish at: 2018-06-01

Comparative Study Entered New Approach FMV and Control SFR for Active Compensation of Harmonic Currents in Shunt Active Power Filter

10.11591/ijra.v7i2.pp119-128
Loutfi Benyettou
In this article, we discuss the problem of degradation of current in electrical installations, which follows directly from the proliferation of non-linear loads, to solve it, we used a two-level inverter as a parallel active filter, which injects current harmonics at the connection point with two compensation methods the method of instantaneous active and reactive power (pq method and pq method with MVF) method binds to the repository synchronization. We will highlight two control strategies by hysteresis and PWM. Simulation results using Blok set Power System (PBS)/ Simulink Matlab show reduced THD in accordance with standard IEEE-519.
Volume: 7
Issue: 2
Page: 119-128
Publish at: 2018-06-01

Transceiver Design for MIMO Systems with Individual Transmit Power Constraints

10.11591/ijece.v8i3.pp1583-1595
Raja Muthalagu
This paper investigate the transceiver design for single-user multiple-input multipleoutput system (SU-MIMO). Joint transceiver design with an improper modulation is developed based on the minimum total mean-squared error (TMSE) criterion under two different cases. One is equal power allocation (EPA) and other is the power constraint that jointly meets both EPA and total transmit power constraint (TTPC) (i.e ITPC). Transceiver is designed based on the assumption that both the perfect and imperfect channel state information (CSI) is available at both the transmitter and receiver. The simulation results show the performance improvement of the proposed work over conventional work in terms of bit error rate (BER).
Volume: 8
Issue: 3
Page: 1583-1595
Publish at: 2018-06-01

Application of Sliding Mode Control Technique to Regulate DC/DC Boost Converters in Systems Exploiting Photovoltaic Power Generation

10.11591/ijra.v7i2.pp96-107
Le Tien Phong , Ngo Duc Minh
This paper introduces a new method, called IB-SMC method, to control DC/DC boost converters in systems exploiting photovoltaic power generation. This method combines the sliding mode control technique and iterative-bisectional  technique in the maximum power point tracker to change operations modes of photovoltaic power generation. The IB-SMC controller uses voltage sliding surface to evaluate the relation of instantaneous voltage at the input converter and instantaneous voltage at the maximum power point. Using information about the power of electromagnetic radiation from a pyranometer and temperature from a temperature sensor, the sliding surface and hyteresis band are changed by practically operational conditions that help improving energy efficiency of the process exploiting PVg. Simulations are carried out by Matlab/Simulink that show the ability to ensure dynamic stability by tracking instaneous maximum power point at any time whenever having any change of the operational condition, static stability by maintaining the operation point at maximum power point whenever not have any change of the operational condition and help to bring out approximately absolute energy efficiency.
Volume: 7
Issue: 2
Page: 96-107
Publish at: 2018-06-01

Analysis of ANFIS MPPT Controllers for Partially Shaded Stand Alone Photovoltaic System with Multilevel Inverter

10.11591/ijra.v7i2.pp140-148
T. Ramesh , R. Saravanan , S. Sekar
This work presents a unique combination of an boost converter  run by a set of two photovoltaic panels (PV) with a MPPT, suitable to guarantee MPP even under partial shadowed conditions, managed by an adaptive neuro fuzzy inference system (ANFIS) trained by the training data derived from a Perturb and observation (P&O) conventional algorithm. The single phase cascaded H bridge five-level inverter (CHI) driven by the individual outputs of the boost converter, with selective harmonic elimination scheme to eliminate typically the seventh order harmonics. Simulation was carried out in the MATLAB/SIMULINK environment validated the proposed scheme. It has been thus established; by both simulations the ANFIS model of MPPT scheme outperforms other schemes of conventional control algorithm.
Volume: 7
Issue: 2
Page: 140-148
Publish at: 2018-06-01

Optimal Reactive Power Dispatch using Crow Search Algorithm

10.11591/ijece.v8i3.pp1423-1431
Lakshmi M , Ramesh Kumar A
The optimal reactive power dispatch is a kind of optimization problem that plays a very important role in the operation and control of the power system. This work presents a meta-heuristic based approach to solve the optimal reactive power dispatch problem. The proposed approach employs Crow Search algorithm to find the values for optimal setting of optimal reactive power dispatch control variables. The proposed way of approach is scrutinized and further being tested on the standard IEEE 30-bus, 57-bus and 118-bus test system with different objectives which includes the minimization of real power losses, total voltage deviation and also the enhancement of voltage stability. The simulation results procured thus indicates the supremacy of the proposed approach over the other approaches cited in the literature.
Volume: 8
Issue: 3
Page: 1423-1431
Publish at: 2018-06-01

Neural Network Based MPPT Controller for Solar PV Connected Induction Motor

10.11591/ijra.v7i2.pp129-139
T. Shanthi
In this paper, Maximum Power Point Tracking Controller is designed based on Neural Network Controller (NNC). This controller will sense the speed of a single phase induction motor which is fed from solar panel. Maximum power point tracking (MPPT) algorithm are required in all photovoltaic (PV) system and in order to increase the efficiency of the system, Incremental Conductance algorithm which is an effective algorithm is used to extract maximum power from the solar panel which supplies an Induction motor of 1HP. To step up the voltage available from the solar panel, the SEPIC dc – dc converter is used. The main advantage of the converter is having non-inverted output. The converter acts as an interface between PV array and motor load. The entire system is modeled and simulated using MATLAB/Simulink  software.
Volume: 7
Issue: 2
Page: 129-139
Publish at: 2018-06-01

Democratic Perception and Attitudes of the Pre-Service Music Teachers in Turkey

10.11591/ijere.v7i2.13141
Hatice Onuray Eğilmez , Özgür Eğilmez , Doruk Engür
Democracy, a lifestyle as much as it is a form of government, begins to be learned in the family. The youth observe and acquire the democratic attitudes of their parents. The task of passing it on to the new generations and helping them acquire democratic values is the mission of schools, namely teachers. It is a commonly known fact that developmental level of countries shows parallelism with the democratic attitudes of individuals. It is important to understand the democratic perceptions and attitudes of teachers who are responsible for positioning democratic structure and thus raising the democratic level of countries. For this reason, the research aims to examine the democratic perceptions and attitudes of music teacher candidates in terms of some variables. Data collected using the democratic attitude scale were analyzed using t-test, Kruskal-Wallis H test, and Spearman’s correlation coefficient. Results showed that attitude scores did not change according to gender, level of parents’ education or the year students were in. Scale scores were negatively correlated with the amount of parents’ income. There was no correlation between the students’ GPAs and the scale scores. Music teaching requires a democratic environment intrinsically; therefore, the democratic perceptions and attitudes of the music teacher candidates who will carry out the music lessons in which they should maintain the democratic environment must be determined. As aforementioned notions suggest, this study is of the essence since the results will shed light on the academic staff in the institutions that train music teachers.
Volume: 7
Issue: 2
Page: 100–108
Publish at: 2018-06-01

Long-Range Monitoring System with PDMS Material

10.11591/ijeecs.v10.i3.pp974-979
Norsaidah Muhamad Nadzir , M. K. A. Rahim , F. Zubir , H. A. Majid
This paper describes the development of a long range monitoring system that integrates Cottonwood: UHF Long Distance RFID reader module with Raspberry Pi 3. When a UHF RFID tag is within the UHF RFID reader antenna’s range, the unique ID of the tag will be transferred to the Raspberry Pi 3 to be processed. Then, the data will be sent over to the database wirelessly to be managed, stored, and displayed. The paper also describes the measurement done to determine the most suitable thickness of PDMS material so that it could be incorporated as a wearable transponder. After the result is calculated and tabulated, it can be concluded that the most suitable thickness of PDMS material for the transponder is 8 mm.
Volume: 10
Issue: 3
Page: 974-979
Publish at: 2018-06-01

Neural Network and Local Search to Solve Binary CSP

10.11591/ijeecs.v10.i3.pp1319-1330
Adil Bouhouch , Hamid Bennis , Chakir Loqman , Abderrahim El Qadi
Continuous Hopfield neural Network (CHN) is one of the effective approaches to solve Constrain Satisfaction Problems (CSPs). However, the main problem with CHN is that it can reach stabilisation with outputs in real values, which means an inconsistent solution or an incomplete assignment of CSP variables. In this paper, we propose a new hybrid approach combining CHN and min-conflict heuristic to mitigate these problems. The obtained results  show  an  improvement  in  terms  of  solution  quality,  either  our approach achieves feasible soluion with a high rate of convergence, furthermore, this approach can also enhance theperformance more than conventional CHN in some cases, particularly, when the network crashes.
Volume: 10
Issue: 3
Page: 1319-1330
Publish at: 2018-06-01
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