Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences Commons™

Open Access. Powered by Scholars. Published by Universities.®

Electrical and Computer Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1831 - 1860 of 5278

Full-Text Articles in Computer Sciences

A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh Jan 2019

A Novel Accuracy Assessment Model For Video Stabilization Approaches Based On Background Motion, Md Alamgir Hossain, Tien-Dung Nguyen, Eui Nam Huh

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a new accuracy measurement model for the video stabilization method based on background motion that can accurately measure the performance of the video stabilization algorithm. Undesired residual motion present in the video can quantitatively be measured by the pixel by pixel background motion displacement between two consecutive background frames. First of all, foregrounds are removed from a stabilized video, and then we find the two-dimensional flow vectors for each pixel separately between two consecutive background frames. After that, we calculate a Euclidean distance between these two flow vectors for each pixel one by one, which …

Go to article

A Fast And Memory-Efficient Two-Pass Connected-Component Labeling Algorithm For Binary Images, Bilal Bataineh Jan 2019

A Fast And Memory-Efficient Two-Pass Connected-Component Labeling Algorithm For Binary Images, Bilal Bataineh

Turkish Journal of Electrical Engineering and Computer Sciences

Connected-component labeling is an important process in image analysis and pattern recognition. It aims to deduct the connected components by giving a unique label value for each individual component. Many algorithms have been proposed, but they still face several problems such as slow execution time, falling in the pipeline, requiring a huge amount of memory with high resolution, being noisy, and giving irregular images. In this work, a fast and memory-efficient connected-component labeling algorithm for binary images is proposed. The proposed algorithm is based on a new run-base tracing method with a new resolving process to find the final equivalent …

Go to article

An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N Jan 2019

An Improved Tree Model Based On Ensemble Feature Selection For Classification, Chandralekha M, Shenbagavadivu N

Turkish Journal of Electrical Engineering and Computer Sciences

Researchers train and build specific models to classify the presence and absence of a disease and the accuracy of such classification models is continuously improved. The process of building a model and training depends on the medical data utilized. Various machine learning techniques and tools are used to handle different data with respect to disease types and their clinical conditions. Classification is the most widely used technique to classify disease and the accuracy of the classifier largely depends on the attributes. The choice of the attribute largely affects the diagnosis and performance of the classifier. Due to growing large volumes …

Go to article

Performance Tuning For Machine Learning-Based Software Development Effort Prediction Models, Egemen Ertuğrul, Zaki̇r Baytar, Çağatay Çatal, Ömer Can Muratli Jan 2019

Performance Tuning For Machine Learning-Based Software Development Effort Prediction Models, Egemen Ertuğrul, Zaki̇r Baytar, Çağatay Çatal, Ömer Can Muratli

Turkish Journal of Electrical Engineering and Computer Sciences

Software development effort estimation is a critical activity of the project management process. In this study, machine learning algorithms were investigated in conjunction with feature transformation, feature selection, and parameter tuning techniques to estimate the development effort accurately and a new model was proposed as part of an expert system. We preferred the most general-purpose algorithms, applied parameter optimization technique (GridSearch), feature transformation techniques (binning and one-hot-encoding), and feature selection algorithm (principal component analysis). All the models were trained on the ISBSG datasets and implemented by using the scikit-learn package in the Python language. The proposed model uses a multilayer …

Go to article

A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan Jan 2019

A Polarity Calculation Approach For Lexicon-Based Turkish Sentiment Analysis, Gökhan Yurtalan, Murat Koyuncu, Çi̇ğdem Turhan

Turkish Journal of Electrical Engineering and Computer Sciences

Sentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across to the people about an object or event. It generally uses natural language processing and/or artificial intelligence techniques for processing electronic documents and mining the opinion specified in the content. In recent years, researchers have conducted many successful sentiment analysis studies for the English language which consider many words and word groups that set emotion polarities arising from the English grammar structure, and then use datasets to test their performance. However, there are only a limited number of studies for the Turkish …

Go to article

Online Network Coding-Based Multicast Routing In Multichannel Multiradio Wireless Mesh Networks, Leili Farzinvash Jan 2019

Online Network Coding-Based Multicast Routing In Multichannel Multiradio Wireless Mesh Networks, Leili Farzinvash

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we consider the problem of online multicast routing in multichannel multiradio wireless mesh networks (WMNs). We propose an efficient online algorithm, namely zone-based multicast routing (ZBMR), which exploits network coding and wireless broadcast advantage. In the proposed algorithm, to investigate the acceptance of an arrived session in polynomial time, the WMN is divided into some zones. The derived zones are processed sequentially, where the zone processing is defined as connecting the receivers in a given zone to the session. The main challenge in this scheme is to enable data transmission to the receivers in each zone. If …

Go to article

Low-Latency And Energy-Efficient Scheduling In Fog-Based Iot Applications, Dadmehr Rahbari, Mohsen Nickray Jan 2019

Low-Latency And Energy-Efficient Scheduling In Fog-Based Iot Applications, Dadmehr Rahbari, Mohsen Nickray

Turkish Journal of Electrical Engineering and Computer Sciences

In today's world, the internet of things (IoT) is developing rapidly. Wireless sensor network (WSN) as an infrastructure of IoT has limitations in the processing power, storage, and delay for data transfer to cloud. The large volume of generated data and their transmission between WSNs and cloud are serious challenges. Fog computing (FC) as an extension of cloud to the edge of the network reduces latency and traffic; thus, it is very useful in IoT applications such as healthcare applications, wearables, intelligent transportation systems, and smart cities. Resource allocation and task scheduling are the NP-hard issues in FC. Each application …

Go to article

An Improved Form Of The Ant Lion Optimization Algorithm For Image Clustering Problems, Meti̇n Toz Jan 2019

An Improved Form Of The Ant Lion Optimization Algorithm For Image Clustering Problems, Meti̇n Toz

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an improved form of the ant lion optimization algorithm (IALO) to solve image clustering problem. The improvement of the algorithm was made using a new boundary decreasing procedure. Moreover, a recently proposed objective function for image clustering in the literature was also improved to obtain well-separated clusters while minimizing the intracluster distances. In order to accurately demonstrate the performances of the proposed methods, firstly, twenty-three benchmark functions were solved with IALO and the results were compared with the ALO and a chaos-based ALO algorithm from the literature. Secondly, four benchmark images were clustered by IALO and the …

Go to article

Farsi Document Image Recognition System Using Word Layout Signature, Cem Ergün, Sajedeh Norozpour Jan 2019

Farsi Document Image Recognition System Using Word Layout Signature, Cem Ergün, Sajedeh Norozpour

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a new representation of Farsi words is proposed to present the keyword spotting problems in Farsi document image retrieval. In this regard, we define a signature for each Farsi word based on the word connected component layout. The mentioned signature is shown as boxes, and then, by sketching vertical and horizontal lines, we construct a grid of each word to provide a new descriptor. One of the advantages of this method is that it can be used for both handwritten and machine-printed texts. Finally, to evaluate the performance of our system in comparison to other methods, a …

Go to article

Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon Jan 2019

Hybix: A Novel Encoding Bitmap Index For Space- And Time-Efficient Query Processing, Naphat Keawpibal, Ladda Preechaveerakul, Sirirut Vanichayobon

Turkish Journal of Electrical Engineering and Computer Sciences

A bitmap-based index is an effective and efficient indexing method for answering selective queries in a read-only environment. It offers improved query execution time by applying low-cost Boolean operators on the index directly, before accessing raw data. A drawback of the bitmap index is that index size increases with the cardinality of indexed attributes, which additionally has an impact on a query execution time. This impact is related to an increase of query execution time due to the scanning of bitmap vectors to answer the queries. In this paper, we propose a new encoding bitmap index, called the HyBiX bitmap …

Go to article

Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan Jan 2019

Dynamic Physarum Solver: A Bio-Inspired Shortest Path Method Of Dynamically Changing Graphs, Hi̇lal Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

In dynamic graphs, edge weights of the graph change with time and solving the shortest path problem in such graphs is an important real-world problem. The studies in the literature require excessive computational time for computing the dynamic shortest path since determining changing edge weights is difficult especially when the graph size becomes large. In this paper, we propose a dynamic bio-inspired algorithm for finding the dynamic shortest path for large graphs based on Physarum Solver, which is a shortest path algorithm for static graphs. The proposed method is evaluated using three different large graph models representing diverse real-life applications. …

Go to article

An Approach To Improve The Performance Of Cooperative Unmanned Vehicle Team, Ömer Ci̇han Kivanç Jan 2019

An Approach To Improve The Performance Of Cooperative Unmanned Vehicle Team, Ömer Ci̇han Kivanç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a method based on optimal energy management is proposed in order to improve the operational and tactical abilities of collaborative unmanned vehicle teams. Collaborative unmanned systems are used in surveillance, tracking, and military operations. The optimal assignment of these tasks requires cooperation among the vehicles in order to generate a strategy that is efficient with respect to overall mission duration and satisfies all problem constraints. The key motivation behind this paper is to design an unmanned vehicle team that mitigates the disadvantages caused by the structures and characteristics of unmanned ground vehicles (UGVs) and unmanned aerial vehicles …

Go to article

Multiellipsoidal Extended Target Tracking With Known Extent Using Sequential Monte Carlo Framework, Süleyman Fati̇h Kara, Emre Özkan Jan 2019

Multiellipsoidal Extended Target Tracking With Known Extent Using Sequential Monte Carlo Framework, Süleyman Fati̇h Kara, Emre Özkan

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we consider a variant of the extended target tracking (ETT) problem, namely the multiellipsoidal ETT problem. In multiellipsoidal ETT, target extent is represented by multiple ellipses, which correspond to the origin of the measurements on the target surface. The problem involves estimating the target's kinematic state and solving the association problem between the measurements and the ellipses. We cast the problem in a sequential Monte Carlo (SMC) framework and investigate different marginalization strategies to find an efficient particle filter. Under the known extent assumption, we define association variables to find the correct association between the measurements and …

Go to article

Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç Jan 2019

Optimal Training And Test Sets Design For Machine Learning, Burkay Genç, Hüseyi̇n Tunç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we describe histogram matching, a metric for measuring the distance of two datasets with exactly the same features, and embed it into a mixed integer programming formulation to partition a dataset into fixed size training and test subsets. The partition is done such that the pairwise distances between the dataset and the subsets are minimized with respect to histogram matching. We then conduct a numerical study using a well-known machine learning dataset. We demonstrate that the training set constructed with our approach provides feature distributions almost the same as the whole dataset, whereas training sets constructed via …

Go to article

Efficient Features For Smartphone-Based Iris Recognition, Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran, Pawan Dubey Jan 2019

Efficient Features For Smartphone-Based Iris Recognition, Ritesh Vyas, Tirupathiraju Kanumuri, Gyanendra Sheoran, Pawan Dubey

Turkish Journal of Electrical Engineering and Computer Sciences

Iris recognition has widely been used in personal authentication problems. Recent advances in iris recognition through visible wavelength images have paved the way for the use of this technology in smartphones. Smartphone-based iris recognition can be of significant use in financial transactions and secure storage of sensitive information. This paper presents a hybrid representation scheme for iris recognition in mobile devices. The scheme is called hybrid because it firstly makes use of Gabor wavelets to reveal the texture present in the normalized iris images, and then extracts statistical features from different partitions of Gabor-processed images. The standard mobile-iris database, called …

Go to article

Plant Disease And Pest Detection Using Deep Learning-Based Features, Muammer Türkoğlu, Davut Hanbay Jan 2019

Plant Disease And Pest Detection Using Deep Learning-Based Features, Muammer Türkoğlu, Davut Hanbay

Turkish Journal of Electrical Engineering and Computer Sciences

The timely and accurate diagnosis of plant diseases plays an important role in preventing the loss of productivity and loss or reduced quantity of agricultural products. In order to solve such problems, methods based on machine learning can be used. In recent years, deep learning, which is especially widely used in image processing, offers many new applications related to precision agriculture. In this study, we evaluated the performance results using different approaches of nine powerful architectures of deep neural networks for plant disease detection. Transfer learning and deep feature extraction methods are used, which adapt these deep learning models to …

Go to article

Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural Jan 2019

Domain Adaptation On Graphs By Learning Graph Topologies: Theoretical Analysis And An Algorithm, Eli̇f Vural

Turkish Journal of Electrical Engineering and Computer Sciences

Traditional machine learning algorithms assume that the training and test data have the same distribution, while this assumption does not necessarily hold in real applications. Domain adaptation methods take into account the deviations in data distribution. In this work, we study the problem of domain adaptation on graphs. We consider a source graph and a target graph constructed with samples drawn from data manifolds. We study the problem of estimating the unknown class labels on the target graph using the label information on the source graph and the similarity between the two graphs. We particularly focus on a setting where …

Go to article

A Joint Image Dehazing And Segmentation Model, Haider Ali, Awal Sher, Nosheen Zikria, Lavdi̇e Rada Ülgen Jan 2019

A Joint Image Dehazing And Segmentation Model, Haider Ali, Awal Sher, Nosheen Zikria, Lavdi̇e Rada Ülgen

Turkish Journal of Electrical Engineering and Computer Sciences

Objects and their feature identification in hazy or foggy weather conditions has been of interest in the last decades. Improving image visualization by removing weather influence factors for easy image postprocessing, such as object detection, has benefits for human assistance systems. In this paper, we propose a novel variational model that will be capable of jointly segmenting and dehazing a given image. The proposed model incorporates atmospheric veil estimation and locally computed denoising constrained surfaces into a level set function by performing a robust and efficient image dehazing and segmentation scheme for both gray and color outdoor images. The proposed …

Go to article

Can Additional Spectral Bands Be Estimated From Aerial Color Images?, Muhammet Ali̇ Dede, Erchan Aptoula, Yakup Genç Jan 2019

Can Additional Spectral Bands Be Estimated From Aerial Color Images?, Muhammet Ali̇ Dede, Erchan Aptoula, Yakup Genç

Turkish Journal of Electrical Engineering and Computer Sciences

Inspired by the surprising performances of deep generative models, in this paper we present the preliminary results of an overly ambitious task: estimating computationally the additional spectral bands of a color aerial image. We have harnessed the expressive power of deep generative models to estimate the distribution of mostly infrared bands of aerial scenes, using only color RGB channels as input. Our approach has been tested from multiple aspects, including the reconstruction error of the additional bands and the effect of estimated bands on scene classification performance, as well as through the transfer potential of the trained network to a …

Go to article

Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding Jan 2019

Efficient Hierarchical Temporal Segmentation Method For Facial Expression Sequences, Jiali Bian, Xue Mei, Yu Xue, Liang Wu, Yao Ding

Turkish Journal of Electrical Engineering and Computer Sciences

Temporal segmentation of facial expression sequences is important to understand and analyze human facial expressions. It is, however, challenging to deal with the complexity of facial muscle movements by finding a suitable metric to distinguish among different expressions and to deal with the uncontrolled environmental factors in the real world. This paper presents a two-step unsupervised segmentation method composed of rough segmentation and fine segmentation stages to compute the optimal segmentation positions in video sequences to facilitate the segmentation of different facial expressions. The proposed method performs localization of facial expression patches to aid in recognition and extraction of specific …

Go to article

Low-Cost Multiple Object Tracking For Embedded Vision Applications, Muhammad Imran Shehzad, Fazal Wahab Karam, Shoaib Azmat Jan 2019

Low-Cost Multiple Object Tracking For Embedded Vision Applications, Muhammad Imran Shehzad, Fazal Wahab Karam, Shoaib Azmat

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a low-cost multiple object tracking (MOT) technique by employing a novel appearance update model for object appearance modeling using K-means. The state-of-the-art work has attained a very high accuracy without considering the real-time aspects necessitated by currently trending embedded vision platforms. The major research on multiple object tracking is used to update the appearance model in every frame while discounting its persistent nature. The proposed appearance update model reduces the computational cost of the state-of-the-art MOT 6-fold by exploiting this facet of persistent appearance over the sequence of frames. To ensure accuracy, the proposed model is tested …

Go to article

An Efficient Retrieval Algorithm Of Encrypted Speech Based On Inverse Fast Fourier Transform And Measurement Matrix, Qiuyu Zhang, Zixian Ge, Liang Zhou, Yongbing Zhang Jan 2019

An Efficient Retrieval Algorithm Of Encrypted Speech Based On Inverse Fast Fourier Transform And Measurement Matrix, Qiuyu Zhang, Zixian Ge, Liang Zhou, Yongbing Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present an efficient retrieval algorithm for encrypted speech based on an inverse fast Fourier transform and measurement matrix. Our approach improves query performance, as well as retrieval efficiency and accuracy, compared to existing content-based encrypted speech retrieval methods. Our proposed algorithm constructs a perceptual hash scheme using perceptual hash sequences from original speech files. By classifying the sequences and applying run-length compression, we decrease the cloud storage required for the hash index. We secure the speech database by encrypting it with Henon chaos scrambling, which offers excellent resistance to attacks. Experimental results show that the robustness, …

Go to article

Classification Of The Likelihood Of Colon Cancer With Machine Learning Techniques Using Ftir Signals Obtained From Plasma, Suat Toraman, Mustafa Gi̇rgi̇n, Bi̇lal Üstündağ, İbrahi̇m Türkoğlu Jan 2019

Classification Of The Likelihood Of Colon Cancer With Machine Learning Techniques Using Ftir Signals Obtained From Plasma, Suat Toraman, Mustafa Gi̇rgi̇n, Bi̇lal Üstündağ, İbrahi̇m Türkoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Colon cancer is one of the major causes of human mortality worldwide and the same can be said for Turkey. Various methods are used for the determination of cancer. One of these methods is Fourier transform infrared (FTIR) spectroscopy, which has the ability to reveal biochemical changes. The most common features used to distinguish patients with cancer and healthy subjects are peak densities, peak height ratios, and peak area ratios. The greatest challenge of studies conducted to distinguish cancer patients from healthy subjects using FTIR signals is that the signals of cancer patients and healthy subjects are similar. In the …

Go to article

Key Word Extraction For Short Text Via Word2vec, Doc2vec, And Textrank, Jun Li, Guimin Huang, Chunli Fan, Zhenglin Sun, Hongtao Zhu Jan 2019

Key Word Extraction For Short Text Via Word2vec, Doc2vec, And Textrank, Jun Li, Guimin Huang, Chunli Fan, Zhenglin Sun, Hongtao Zhu

Turkish Journal of Electrical Engineering and Computer Sciences

Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The data obtained should provide meaningful, correct, and accurate information. Therefore, all data must be separated into clusters correctly, and the right information from these clusters must be obtained. Having the correct clusters depends on the clustering algorithm that is used. There are many clustering algorithms. The density-based methods are very important among the groups of clustering methods, as they can find arbitrary shapes. An advanced model of the density-based spatial clustering of applications with noise (DBSCAN) algorithm, called fuzzy neighborhood DBSCAN Gaussian means …

Go to article

A Hybrid Sentiment Analysis Method For Turkish, Buket Erşahi̇n, Özlem Aktaş, Deni̇z Kilinç, Mustafa Erşahi̇n Jan 2019

A Hybrid Sentiment Analysis Method For Turkish, Buket Erşahi̇n, Özlem Aktaş, Deni̇z Kilinç, Mustafa Erşahi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a hybrid methodology for Turkish sentiment analysis, which combines the lexicon-based and machine learning (ML)-based approaches. On the lexicon-based side, we use a sentiment dictionary that is extended with a synonyms lexicon. Besides this, we tackle the classification problem with three supervised classifiers, naive Bayes, support vector machines, and J48, on the ML side. Our hybrid methodology combines these two approaches by generating a new lexicon-based value according to our feature generation algorithm and feeds it as one of the features to machine learning classifiers. Despite the linguistic challenges caused by the morphological structure of Turkish, the …

Go to article

Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever Jan 2019

Extending A Sentiment Lexicon With Synonym--Antonym Datasets: Swnettr++, Fati̇h Sağlam, Burkay Genç, Hayri̇ Sever

Turkish Journal of Electrical Engineering and Computer Sciences

In our previous studies on developing a general-purpose Turkish sentiment lexicon, we constructed SWNetTR-PLUS, a sentiment lexicon of 37K words. In this paper, we show how to use Turkish synonym and antonym word pairs to extend SWNetTR-PLUS by almost 33 % to obtain SWNetTR++, a Turkish sentiment lexicon of 49K words. The extension was done by transferring the problem into the graph domain, where nodes are words, and edges are synonym--antonym relations between words, and propagating the existing tone and polarity scores to the newly added words using an algorithm we have developed. We tested the existing and new lexicons …

Go to article

Automatic Landing Of A Low-Cost Quadrotor Using Monocular Vision And Kalman Filter In Gps-Denied Environments, Mohammad Fattahi Sani, Maryam Shoaran, Ghader Karimian Jan 2019

Automatic Landing Of A Low-Cost Quadrotor Using Monocular Vision And Kalman Filter In Gps-Denied Environments, Mohammad Fattahi Sani, Maryam Shoaran, Ghader Karimian

Turkish Journal of Electrical Engineering and Computer Sciences

Unmanned aerial vehicles are becoming an important part of the modern life. Despite some recent advances in GPS-aided navigation of quadrotors, the concern of crash and collision still overshadows their reliability and safety, especially in GPS-denied environments. Therefore, the necessity for developing fully automatic methods for safe, accurate, and independent landing of drones increases over time. This paper investigates the autolanding process by focusing on an accurate and continuous position estimation of the drone using a monocular vision system and the fusion with the inertial measurement unit and ultrasonic sensors' data. An ARUCO marker is used as the landing pad, …

Go to article

A Process-Tolerant Low-Power Adder Architecture For Image Processing Applications, Bharat Garg, G K. Sharma Jan 2019

A Process-Tolerant Low-Power Adder Architecture For Image Processing Applications, Bharat Garg, G K. Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

The aggressive CMOS technology scaling in the sub-100-nm regime leads to highly challenging VLSI design due to the presence of unreliable components. The delay failures in arithmetic units are increasing rapidly due to the increased effect of process variation (PV) in scaled technology. This paper introduces a novel process-tolerant low-power adder (Prot-LA) architecture for error-tolerant applications. The proposed Prot-LA architecture segments the operands into two parts and computes addition of the upper parts in carry-propagate, whereas it computes the lower parts in a carry-free manner. In the Prot-LA, the number of bits in carry-propagate and carry-free additions can be reconfigured …

Go to article

Hydrogen Production System With Fuzzy Logic-Controlled Converter, Sali̇h Nacar, Seli̇m Öncü Jan 2019

Hydrogen Production System With Fuzzy Logic-Controlled Converter, Sali̇h Nacar, Seli̇m Öncü

Turkish Journal of Electrical Engineering and Computer Sciences

Electrolyte current must be controlled in the water electrolysis systems. For this purpose, the power converter for the cell stack of the electrolyzer used in industrial hydrogen production is realized. A series resonant converter, which is suitable for high input voltage and low output current applications, is used as power stage of the electrolyzer. The high-frequency transformer is used for the impedance matching. While the system is running, the electrical resistance of the electrolyzer changes continuously; thus, fuzzy logic controller (FLC) is used to control the output current of the power converter. In this study, a 700-W converter prototype is …

Go to article

Fast Nonsingular Terminal Decoupled Sliding-Mode Control Utilizing Time-Varying Sliding Surfaces, Ferhun Yorgancioğlu, Soydan Redif Jan 2019

Fast Nonsingular Terminal Decoupled Sliding-Mode Control Utilizing Time-Varying Sliding Surfaces, Ferhun Yorgancioğlu, Soydan Redif

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a fast form of nonsingular, terminal, decoupled, sliding-mode control, which utilizes time-varying sliding surfaces, is proposed for a class of fourth-order, single-input, multioutput, nonlinear systems. The novel control law features a fast term, in the manner of fast terminal sliding-mode control, which markedly improves the finite-time sliding-mode convergence speed near zero. Numerical simulation results, which are illustrated with a cart-pole inverted pendulum system and a ball-beam system, demonstrate that the proposed control law achieves, in general, favorable transient response and lower steady-state errors compared to state-of-the-art decoupled terminal sliding-mode control methods.

Go to article

First Prev Next Last