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31,456 Article Results

Structural correction of nonlinear dynamics of frequency-controlled induction motor drives

10.11591/ijpeds.v11.i1.pp220-227
Vladimir L. Kodkin , Aleksandr Sergeevich Anikin , Aleksandr Aleksandrovich Baldenkov
Frequency analysis of processes in the frequency-controlled induction motor drive s, as in automatic control systems with dynamic non-linearities, are presented in this paper. For the first time, dynamic formulas of transfer functions of a torque driver in an induction motor with frequency control, taking into account the slip and frequency of the stator voltage, are proposed. Methods for constructing families of frequency characteristics of such electromechanical systems with “frozen” but different values of the frequency of the stator voltage and slip are described. The frequency characteristics corresponding to these transfer functions are constructed in the Simulink application of the MatLab software. Based on results of the analysis the structural correction methods that improve the dynamics of such nonlinear systems are proposed. The nonlinear transfer functions obtained in this work made it possible to substantiate structural solutions that linearize frequency-controlled electric drives and significantly increase their efficiency. This paper is an example of how the initial complicated (but more accurate) interpretation of nonlinearity allowed us to find a new best solution to the problem of controlling a complex dynamic object.
Volume: 11
Issue: 1
Page: 220-227
Publish at: 2020-03-01

Methods for database ciphering

10.11591/ijeecs.v17.i3.pp1499-1505
Maitham Ali Naji , Dalal Abdul Mohsin Hammood , Nuha Abdul Razik Al Debagh
In this paper Caesar and Vigenere methods have been used for table ciphering. Each record has unique and independent keys to the next record to get high security. The cipher text stored in script file that separates the content of fields by semicolon. The second part is the process of creating a new database using the Object called Data Access Object (DAO) and then create table and it is fields. The program gets plaintext of the table by applying the decryption rules of two methods.
Volume: 17
Issue: 3
Page: 1499-1505
Publish at: 2020-03-01

An advance encryption standard cryptosystem in IoT transaction

10.11591/ijeecs.v17.i3.pp1548-1554
Zolidah Kasiran , Shapina Abdullah , Normazlie Mohd Nor
IoT create an ecosystem that can be useful to the world with its various services. That make the security of IoT is more important. This paper presents a proposed technique to secure data transaction from IoT device to other node using cryptography technique. AES cryptography and IoT device model ESP8266 is used as a client to send data to a server via HTTP protocol. Security performance matrices used eavesdropping attack with Wireshark sniffing and brute-force attack. will be simulated to the proposed method in order to ensure if there is any possibility it can be cracked using those attacks and to evaluate the performance of ESP8266, several experiments were be conducted. Result gather from this experiment was evaluated based on processing time to see the effectiveness of the platform compare to different data size used while adapting this technique.
Volume: 17
Issue: 3
Page: 1548-1554
Publish at: 2020-03-01

Design and operation of closed-loop triple-deck buck-boost converter with high gain soft switching

10.11591/ijpeds.v11.i1.pp523-529
S. Narasimha , Surender Reddy Salkuti
This paper presents the design and operation of three-stage buck-boost converter with high gain soft switching using closed loop proportional integral (PI) controller. The proposed converter is designed by arranging three identical buck-boost converters working in parallel. The converter units are connected to each other by an inductor as a bridge. This inductor plays a vital role in soft switching operation of converter by maintaining the voltage applied to switches at zero voltage at switching intervals, i.e., the zero-voltage switching (ZVS). The closed-loop system is designed by PI controller, and it maintains the output constant irrespective of changes in input, and the system becomes stable. The proposed converter is efficient in reducing switching losses, leading to improved converter efficiency. Due to parallel operation of three identical converters, the output voltage and input current contain fewer ripples than those of a single converter with same specifications. Proposed converter is more economical and reliable with simpler structure as it utilizes only two inductors as extra elements. The design and analysis of proposed circuit has been carried out in MATLAB Simulink by operating the circuit in various modes.
Volume: 11
Issue: 1
Page: 523-529
Publish at: 2020-03-01

Performance enhancements of DFIG wind turbine using fuzzy-feedback linearization controller augmented by high-gain observer

10.11591/ijpeds.v11.i1.pp10-23
Kada Boureguig , Abdellah Mansouri , Ahmed Chouya
This paper proposes a feedback linearization control of doubly fed induction generator based wind energy systems for improving decoupled control of the active and reactive powers stator. In order to enhance dynamic performance of the controller studied, the adopted control is reinforced by a fuzzy logic controller. This approach is designed without any model of rotor flux estimation. The difficulty of measuring of rotor flux is overcome by using high gain observer. The stability of the nonlinear observer is proved by the Lyapunov theory. Numerical simulations using MATLAB-SIMULINK shown clearly the robustness of the proposed control, particularly to the disturbance rejection and parametric variations compared with the conventional method.
Volume: 11
Issue: 1
Page: 10-23
Publish at: 2020-03-01

Design of fractional order controllers using constrained optimization and reference tracking method

10.11591/ijpeds.v11.i1.pp291-301
Manoj D Patil , K. Vadirajacharya , Swapnil Khubalkar
In recent times, fractional order controllers are gaining more interest. There are several fractional order controllers are available in literature. Still, tuning of these controllers is one of the main issues which the control community is facing. In this paper, online tuning of five dierent fractional order controllers is discussed viz. tilted proportional-integral-derivative (T-PID) controller, fractional order proportional-integral (FO-PI) controller, fractional order proportional-derivative (FO-PD) controller, fractional order proportional-integral-derivative (FO-PID) controller. A reference tracking method is proposed for tuning of fractional order controllers. First order with dead time (FOWDT) system is used to check feasibility of the control strategy.
Volume: 11
Issue: 1
Page: 291-301
Publish at: 2020-03-01

An ELM-based single input rule module and its application in power generation

10.11591/ijpeds.v11.i1.pp359-366
Chong Tak Yaw , Shen Young Wong , Keem Sian Yap
Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. In traditional fuzzy inference method which was the "if-then" rules, all the input and output objects were assigned to antecedent and consequent component respectively. However, a major dilemma was that the fuzzy rules' number kept increasing until the system and arrangement of the rules became complicated. Therefore, the single input rule modules connected type fuzzy inference (SIRM) method where consociated the output of the fuzzy rules modules significantly. In this paper, we put forward a novel single input rule modules based on extreme learning machine (denoted as SIRM-ELM) for solving data regression problems. In this hybrid model, the concept of SIRM is applied as hidden neurons of ELM and each of them represents a single input fuzzy rules. Hence, the number of fuzzy rule and the number of hidden neuron of ELM are the same. The effectiveness of proposed SIRM-ELM model is verified using sigmoid activation functions based on several benchmark datasets and a NOx emission of power generation plant.  Experimental results illustrate that our proposed SIRM-ELM model is capable of achieving small root mean square error, i.e., 0.027448 for prediction of NOx emission.
Volume: 11
Issue: 1
Page: 359-366
Publish at: 2020-03-01

A wind turbine sensorless automatic control systems, analysis, modelling and development of IDA-PBC method

10.11591/ijpeds.v11.i1.pp45-55
Hamiani Hichem , Mansouri Abdellah , Tadjeddine Ali Abderrazak , Belaidi Abdelkader , Salim Ramzi
Several non-linear controls are developed for controlling a wind energy conversion system equipped with a DFIG double feed asynchronous generator. Exploitation of the aerodynamic power captured by the turbine gives a new instruction to the controller based on passivity by keeping the hypersynchronous regime of the DFIG. An adaptive observer MRAS was developed for the considered as a structure in which the rotor speed is estimated from the measurement of stator and rotor currents. Our goal is to maximize active power, minimize construction costs in order to control wind turbine systems using our passivity and observation method. Best results were obtained using sensorless MPPT and IDA-PBC methods.
Volume: 11
Issue: 1
Page: 45-55
Publish at: 2020-03-01

Development of option c measurement and verification model using hybrid artificial neural network-cross validation technique to quantify saving

10.11591/ijai.v9.i1.pp25-32
Wan Nazirah Wan Md Adnan , Nofri Yenita Dahlan , Ismail Musirin
This paper aims to develop a hybrid artificial neural network for Option C Measurement and Verification model to predict monthly building energy consumption. In this work, baseline energy model development using artificial neural networks embedded with artificial bee colony optimization and cross validation technique for a small dataset were considered. Artificial bee colony optimization with coefficient of correlation fitness function was used in optimizing the neural network training process and selecting the optimal values of initial weights and biases. Working days, class days and cooling degree days were used as input meanwhile monthly electricity consumption as an output of artificial neural network. The results indicated that this hybrid artificial neural network model provided better prediction results compared to the other model. The best model with the highest value of coefficient of correlation was selected as the baseline model hence is used to determine the saving. 
Volume: 9
Issue: 1
Page: 25-32
Publish at: 2020-03-01

Large-scale image-to-video face retrieval with convolutional neural network features

10.11591/ijai.v9.i1.pp40-45
Imane Hachchane , Abdelmajid Badri , Aïcha Sahel , Yassine Ruichek
Convolutional neural network features are becoming the norm in instance retrieval. This work investigates the relevance of using an of the shelf object detection network, like Faster R-CNN, as a feature extractor for an image-to-video face retrieval pipeline instead of using hand-crafted features. We use the objects proposals learned by a Region Proposal Network (RPN) and their associated representations taken from a CNN for the filtering and the re-ranking steps. Moreover, we study the relevance of features from a finetuned network. In addition to that we explore the use of face detection, fisher vector and bag of visual words with those CNN features. We also test the impact of different similarity metrics. The results obtained are very promising.
Volume: 9
Issue: 1
Page: 40-45
Publish at: 2020-03-01

Fuzzy logic based fan controller of indoor air purifier fan

10.11591/ijeecs.v17.i3.pp1266-1274
Ertie Cusipag Abana , Mark Jerson Palatan , Christian Paolo Pascual , Chia Mae Mateos , Sheree Anne Galasinao
Indoor air purifier (IAP) has been developed by various companies worldwide to address indoor air pollution. The manufacturers of these air purifiers rarely concentrate in controlling the rotation speed of the fan which results in the use of traditional control techniques wherein some still relies on human intervention. In this paper, Fuzzy Logic (FL) was applied to control the rotation speed of the fan of an indoor air purifier. The system automatically maintains a suitable fan speed based on the fuzzy values generated on the current environmental condition. The series of testing conducted using the system showed a very high accuracy in the interpretation of dust concentration to its equivalent Air Quality Index (AQI) levels of health concern. For each detected AQI, the system was able to regulate the voltage coming into a motor that controls the speed of the fan. The usage of the fuzzy logic fan controller in the indoor air purifier fan reduced the energy consumption by 41.67%.
Volume: 17
Issue: 3
Page: 1266-1274
Publish at: 2020-03-01

Design of H_∞ for induction motor

10.11591/ijpeds.v11.i1.pp24-33
Ammar issa Ismael , Lafta E. Jumaa , Nisreen Khamas
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of  be less than one.
Volume: 11
Issue: 1
Page: 24-33
Publish at: 2020-03-01

Ozone prediction based on support vector machine

10.11591/ijeecs.v17.i3.pp1461-1466
M. Tanaskuli , Ali N. Ahmed , Nuratiah Zaini , Samsuri Abdullah , Abdoulhdi A. Borhana , N. A. Mardhiah , Mathivanan Mathivanan
The prediction of tropospheric ozone concentrations is very important due to negative effects of ozone on human health, atmosphere and vegetation. Ozone Prediction is an intricate procedure and most of the conventional models cannot provide accurate prediction. Machine Learning techniques have been widely used as an effective tool for prediction. This study is investigating the implementation of Support vector Machine-SVM to predict Ozone concentrations. The results show that the SVM is capable in predicting ozone concentrations with acceptable level of accuracy. Sensitivity analysis has been conducted to show what is the most effective parameters on the proposed model.
Volume: 17
Issue: 3
Page: 1461-1466
Publish at: 2020-03-01

Intrusions detection using optimized support vector machine

10.11591/ijaas.v9.i1.pp62-66
Mehdi Moukhafi , Khalid El Yassini , Bri Seddik
Computer network technologies are evolving fast and the development of internet technology is more quickly, people more aware of the importance of the network security. Network security is main issue of computing because the number attacks are continuously increasing. For these reasons, intrusion detection systems (IDSs) have emerged as a group of methods that combats the unauthorized use of a network’s resources. Recent advances in information technology, specially in data mining, have produced a wide variety of machine learning methods, which can be integrated into an IDS. This study proposes a new method of intrusion detection that uses support vector machine optimizing optimizing by a genetic algorithm. to improve the efficiency of detecting known and unknown attacks, we used a Particle Swarm Optimization algorithm to select the most influential features for learning the classification model.
Volume: 9
Issue: 1
Page: 62-66
Publish at: 2020-03-01

Verifiable secure computation of linear fractional programming using certificate validation

10.11591/ijpeds.v11.i1.pp284-290
Nedal M. Mohammed , Laman R. Sultan , Ahmed A. Hamoud , Santosh S. Lomte
Outsourcing of scientic computations is attracting increasing attention since it enables the customers with limited computing resource and storage devices to outsource the sophisticated computation workloads into powerful service providers. However, it also comes up with some security and privacy concerns and challenges, such as the input and output privacy of the customers, and cheating behaviors of the cloud. Motivated by these issues, this paper focused on privacy-preserving Linear Fractional Programming (LFP) as a typical and practically relevant case for veriable secure multiparty computation. We will investigate the secure and veriable schema with correctness guarantees, by using normal multiparty techniques to compute the result of a computation and then using veriable techniques only to verify that this result was correct.
Volume: 11
Issue: 1
Page: 284-290
Publish at: 2020-03-01
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