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Articles 1231 - 1260 of 3020
Full-Text Articles in Physical Sciences and Mathematics
A Matched E-H Plane T-Junction For X-Band Applications, Ashmi Chakraborty Das, Santanu Dwari, Amit Bage
A Matched E-H Plane T-Junction For X-Band Applications, Ashmi Chakraborty Das, Santanu Dwari, Amit Bage
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a method of moment-based analysis of an E-H plane T-junction to find its scattering parameters. The results show that the network is not matched at its ports. Therefore, matching networks have been included in the structure to establish matching at the ports. The matching structure includes an inductive window at the H-plane arm and a bisected funnel structure at the junction. Results of the modified structure show simultaneous matching at all the four ports at 9 GHz, which makes it suitable for X-band application.
Emi Filter Design Based On The Separated Electromagnetic Interference In Switched Mode Power Supplies, Samet Yalçin, Şükrü Özen, Selçuk Helhel
Emi Filter Design Based On The Separated Electromagnetic Interference In Switched Mode Power Supplies, Samet Yalçin, Şükrü Özen, Selçuk Helhel
Turkish Journal of Electrical Engineering and Computer Sciences
Usage of switch mode power supplies (SMPS) has been increased tremendously in recent years due to their advantages compared to conventional ones. In spite of their advantages, SMPSs cause conducted and radiated emissions due to the fact that they switch on and off at specific frequencies. Electromagnetic interference (EMI) filters are mostly preferred equipment for the reduction of conducted emission for coupled circuits. Improved EMI filter in the literature to suppress both common and differential mode noises sourced by ATX (a sample of SMPS) power supply has been proposed. A proposed filter was designed by use of AWR Microwave Office …
Classification And Regression Analysis Using Support Vector Machine For Classifying And Locating Faults In A Distribution System, Sophi Shilpa Gururajapathy, Hazlie Mokhlis, Hazlee Azil Bin Illias
Classification And Regression Analysis Using Support Vector Machine For Classifying And Locating Faults In A Distribution System, Sophi Shilpa Gururajapathy, Hazlie Mokhlis, Hazlee Azil Bin Illias
Turkish Journal of Electrical Engineering and Computer Sciences
Various fault location methods have been developed in the past to identify the faulty phase, fault type, faulty section, and distance. However, this identification is commonly conducted in a separate manner. An effective fault location should be able to identify all of these at the same time. Therefore, in this work, a method using a support vector machine (SVM) to identify the fault type, faulty section, and distance considering the faulty phase is proposed. The proposed method uses voltage sag magnitude of the distribution system as the main feature for the SVM to identify faults. The fault type is classified …
The Impact Of Transmission Power Levels Set Size On Lifetime Of Wireless Sensor Networks In Smart Grids, Hüseyi̇n Uğur Yildiz
The Impact Of Transmission Power Levels Set Size On Lifetime Of Wireless Sensor Networks In Smart Grids, Hüseyi̇n Uğur Yildiz
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless sensor networks (WSNs) have been confirmed as one of the most promising technologies for many smart grid (SG) applications due to their low complexity and inexpensive costs. A typical WSN is formed with numerous battery limited sensor nodes mounted on critical components of a SG system for monitoring applications. Acquired monitoring data by sensor nodes are conveyed to the base station generally by using multihop communication techniques. WSN-based SG applications encounter severe propagation losses due to extreme channel conditions of the SG environment. In order to reduce possible packet errors caused by channel variations, transmission power control approaches can …
Application Of Acf-Wavelet Feature Extraction For Classification Of Some Artificial Pd Models Of Power Transformer, Vahid Parvin Darabad
Application Of Acf-Wavelet Feature Extraction For Classification Of Some Artificial Pd Models Of Power Transformer, Vahid Parvin Darabad
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, 7 different artificial partial discharge (PD) models of power transformer defect types are built in a high voltage laboratory, and then PD signals are recorded in the whole power frequency cycle to develop a preliminary PD knowledge base. A specific technique is used to extract single PD events from the recorded knowledge base. By application of wavelet transform, different decomposition levels of extracted PD signals are investigated. Feature extraction is performed by application of statistic moments on the autocorrelation function of PD signal decompositions. "Best" features are selected based on the F-test. To evaluate the performance of …
A Frequency-Tuned Magnetic Resonance-Based Wireless Power Transfer System With Near-Constant Efficiency Up To 24 Cm Distance, Seyi̇t Ahmet Si̇s, Selçuk Kavut
A Frequency-Tuned Magnetic Resonance-Based Wireless Power Transfer System With Near-Constant Efficiency Up To 24 Cm Distance, Seyi̇t Ahmet Si̇s, Selçuk Kavut
Turkish Journal of Electrical Engineering and Computer Sciences
In magnetic resonance-based wireless power transfer systems, the main challenge arises from varying distances between coils during power transfer because distance variations ultimately reduce the power transfer efficiency. Frequency-tuned wireless power transfer systems provide an almost-constant output power to the load up to a critical coupling distance. However, the critical coupling distance and power transfer efficiency are dependent on coil size, source, and load resistances. The purpose of this paper is to discuss this dependency with an equivalent circuit model, determine a suitable coil size for given design specifications, and set up a frequency-tuned system that is based on tracking …
Controlling The Speed And Flux Of A Dual Stator Winding Induction Motor Using An Emotional Intelligent Controller And Integration Algorithm, Hojat Moayedirad, Mohammad Ali Shamsi Nejad
Controlling The Speed And Flux Of A Dual Stator Winding Induction Motor Using An Emotional Intelligent Controller And Integration Algorithm, Hojat Moayedirad, Mohammad Ali Shamsi Nejad
Turkish Journal of Electrical Engineering and Computer Sciences
The appropriate efficiency of a dual stator winding squirrel-cage induction motor (DSWIM) is obtained when the ratio of two frequencies feeding the machine is equal to the ratio of the number of poles. In the vector control method, the estimation of flux at low speed is difficult. To solve this problem, researchers have benefited from the free capacity of the two windings of the stator. This makes the motor deviate from its standard operating mode at low speed. The main purpose of the present study is to reduce the power losses of the inverter units in the sensorless DSWIM drive …
Attenuating Saturated-Regulator Operation Effect Of Brushless Dc Motors Through Genetic-Based Fuzzy Logic Estimator, Emre Çeli̇k, Ni̇hat Öztürk
Attenuating Saturated-Regulator Operation Effect Of Brushless Dc Motors Through Genetic-Based Fuzzy Logic Estimator, Emre Çeli̇k, Ni̇hat Öztürk
Turkish Journal of Electrical Engineering and Computer Sciences
As brushless DC motor (BLDCM) speed approaches base speed, current regulators gradually saturate and lose their ability to perform their regulating task, which causes a dramatic fall in the phase currents and motor power. To control the current to a greater extent and avoid power decline, a new reference current generation technique based on a simple fuzzy logic estimator (FLE) is introduced in this paper. According to motor speed and current command, the developed FLE decides the proper commutation angle $\alpha $, which is the angle relative to normal commutation instant used for setting the current slew rate during commutation. …
Adaptive Antisingularity Terminal Sliding Mode Control For A Robotic Arm With Model Uncertainties And External Disturbances, Kiem Nguyen, Tinh Nguyen, Quyen Bui, Minhtuan Pham
Adaptive Antisingularity Terminal Sliding Mode Control For A Robotic Arm With Model Uncertainties And External Disturbances, Kiem Nguyen, Tinh Nguyen, Quyen Bui, Minhtuan Pham
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a radical adaptive terminal sliding mode control method for a robotic arm with model uncertainties and external disturbances is proposed in such a way that the singularity problem is completely dealt with. A radial basis function neural network (RBFNN) with an online weight tuning algorithm is employed to approximate unknown smooth nonlinear dynamic functions caused by the fact that there is no prior knowledge of the robotic dynamic model. Furthermore, a robust control law is utilized in order to eliminate total uncertainty composed of model uncertainties, external disturbances, and the inevitable approximation errors resulting from the finite …
New Optimization Algorithm Inspired By Fluid Mechanics For Combined Economic And Emission Dispatch Problem, Ruyi Dong, Shengsheng Wang
New Optimization Algorithm Inspired By Fluid Mechanics For Combined Economic And Emission Dispatch Problem, Ruyi Dong, Shengsheng Wang
Turkish Journal of Electrical Engineering and Computer Sciences
With the increasing concern over environmental protection, the combined economic emission dispatch (CEED) problem has received much attention. It needs to minimize both fuel cost and emission pollution. This study aims to propose a new metaheuristic algorithm inspired by fluid mechanics to solve the CEED problem with the weighted sum method. The new algorithm simulates the inverse process of fluid flowing spontaneously from high pressure to low pressure, similar to the optimization process of the CEED problem. When applied in two real-world cases, the new algorithm achieves better performance compared with other algorithms in the literature.
Estimating The Selectivity Of Like Queries Using Pattern-Based Histograms, Mehmet Ayti̇mur, Ali̇ Çakmak
Estimating The Selectivity Of Like Queries Using Pattern-Based Histograms, Mehmet Ayti̇mur, Ali̇ Çakmak
Turkish Journal of Electrical Engineering and Computer Sciences
Accurate cost and time estimation of a query is one of the major success indicators for database management systems. SQL allows the expression of flexible queries on text-formatted data. The LIKE operator is used to search for a specified pattern (e.g., LIKE "luck %") in a string database. It is vital to estimate the selectivity of such flexible predicates for the query optimizer to choose an efficient execution plan. In this paper, we study the problem of estimating the selectivity of a LIKE query predicate over a bag of strings. We propose a new type of pattern-based histogram structure to …
A Distributed Admm Approach For Energy-Efficient Resource Allocation In Mobile Edge Computing, Weiwei Fang, Wenchen Zhou, Yangyang Li, Xuening Yao, Feng Xue, Naixue Xiong
A Distributed Admm Approach For Energy-Efficient Resource Allocation In Mobile Edge Computing, Weiwei Fang, Wenchen Zhou, Yangyang Li, Xuening Yao, Feng Xue, Naixue Xiong
Turkish Journal of Electrical Engineering and Computer Sciences
Mobile edge computing (MEC) is a new promising technique to provide cloud-computing capabilities at the edge of cellular networks in close proximity to mobile users. In this paper, we consider joint optimization of the communication and computation resources in a multiuser, multiserver MEC system. The objective of this optimization problem is to minimize the total energy consumption of mobile devices under the time-sharing constraint. Given the fact that no coordination is involved between mobile devices, we propose a light-weight and decentralized algorithm based on the alternating direction method of multipliers (ADMM) framework. Experimental results demonstrate that the proposed algorithm performs …
Artificial Immune System Based Wastewater Parameter Estimation, Cengi̇z Sertkaya, Ni̇lüfer Yurtay
Artificial Immune System Based Wastewater Parameter Estimation, Cengi̇z Sertkaya, Ni̇lüfer Yurtay
Turkish Journal of Electrical Engineering and Computer Sciences
The basis of a wastewater treatment system is to achieve the desired characteristics of the wastewater treatment process. An estimation of the obtained wastewater treatment characteristics provides the information needed to set up the current process steps, and it is important to have an optimum treatment. In this study, an artificial immune system (AIS) structure is developed to estimate important wastewater output parameters such as pH, DBO, DQO, and SS for the first time. The proposed AIS models are based on the clonal selection principle, and the dataset is provided from the University of California Irvine (UCI) Machine Learning Library. …
Rapid Translation Of Finite-Element Theory Into Computer Implementation Based On A Descriptive Object-Oriented Programming Approach, Murat Yilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we present a framework for rapid prototyping of finite element (FE) theory for computer implementations. For this purpose, we propose an object-oriented (OO) application programming interface in the form of a domain-specific modeling language (DSML). In contrast to the traditional OO approach, the proposed framework deliberately avoids the use of subclassing for concrete implementations of node and element classes; it uses external objects, namely descriptors, instead. The descriptive design of the DSML provides developers with generic programming support for the construction and solution of discretization schemes, in the context of partial differential equations, in a self-explanatory syntax. …
Influence Maximization In Social Networks: An Integer Programming Approach, Muhammed Emre Keski̇n, Mehmet Güray Güler
Influence Maximization In Social Networks: An Integer Programming Approach, Muhammed Emre Keski̇n, Mehmet Güray Güler
Turkish Journal of Electrical Engineering and Computer Sciences
The use of social networks has been spreading rapidly in recent years. There is a growing interest in influence maximization in social networks, especially after observing that the effects of social events of the Arab Spring, Gezi events of Turkey, uprising in Ukraine, etc. have been built by the help of social networks. Consequently, many institutions like political parties or commercial firms are willing to spread their messages throughout social networks. There are many studies that concentrate on finding the most influential initial nodes, called seeds, which maximize the spread of an intended message over the social network. However, most …
Improvement Of Heart Attack Prediction By The Feature Selection Methods, Hi̇dayet Takci
Improvement Of Heart Attack Prediction By The Feature Selection Methods, Hi̇dayet Takci
Turkish Journal of Electrical Engineering and Computer Sciences
Prediction of a heart attack is very important since it is one of the leading causes of sudden death, especially in low-income countries. Although cardiologists use traditional clinical methods such as electrocardiography and blood tests for heart attack prediction, computer aided diagnosis systems that use machine learning methods are also in use for this task. In this study, we used machine learning and feature selection algorithms together. Our aim is to determine the best machine learning method and the best feature selection algorithm to predict heart attacks. For this purpose, many machine learning methods with optimum parameters and several feature …
Estimating Left Ventricular Volume With Roi-Based Convolutional Neural Network, Feng Zhu
Estimating Left Ventricular Volume With Roi-Based Convolutional Neural Network, Feng Zhu
Turkish Journal of Electrical Engineering and Computer Sciences
The volume of the human left ventricular (LV) chamber is an important indicator for diagnosing heart disease. Although LV volume can be measured manually with cardiac magnetic resonance imaging (MRI), the process is difficult and time-consuming for experienced cardiologists. This paper presents an end-to-end segmentation-free method that estimates LV volume from MRI images directly. The method initially uses Fourier transform and a regression filter to calculate the region of interest that contains the LV chambers. Then convolutional neural networks are trained to estimate the end-diastolic volume (EDV) and end-systolic volume (ESV). The resulting models accurately estimate the EDV and ESV …
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a transformer incipient fault diagnosis model has been developed with the help of an artificial neural network (ANN), taking into account the difference in the energy required to produce the different fault gases. The key fault gases are indicative of the fault type prevailing in the transformer. However, in conventional studies, the energy difference in fault gas formation is not considered while adopting the key gas method for fault diagnosis. In this work, a weighting factor has been used to take into account this relative difference in energy requirement for various fault gas formations. The fault gas …
A New Method Based On Pixel Density In Salt And Pepper Noise Removal, Uğur Erkan, Levent Gökrem
A New Method Based On Pixel Density In Salt And Pepper Noise Removal, Uğur Erkan, Levent Gökrem
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we deliver a new method to remove salt and pepper noise, which we refer to as based on pixel density filter (BPDF). The first step of the method is to determine whether or not a pixel is noisy, and then we decide on an adaptive window size that accepts the noisy pixel as the center. The most repetitive noiseless pixel value within the window is set as the new pixel value. By using 18 test images, we give the results of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), image enhancement factor (IEF), standard median filter (SMF), adaptive …
Blood Glucose Control Using An Abc Algorithm-Based Fuzzy-Pid Controller, Seli̇m Soylu, Kenan Danişman
Blood Glucose Control Using An Abc Algorithm-Based Fuzzy-Pid Controller, Seli̇m Soylu, Kenan Danişman
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a Mamdani-type fuzzy controller is proposed as the controller part of an artificial pancreas. The controller is optimized with the artificial bee colony optimization algorithm. The glucose{insulin regulatory system, based on a nonlinear differential model in the presence of delay, is used both for virtual patient and healthy person data. The main target of the controller is to mimic a blood glucose concentration profile of the healthy person with exogenous insulin infusion. Simulations are performed to assess the control function in terms of tracking the blood glucose concentration profile of the healthy person and minimizing errors. To …
Last Level Cache Partitioning Via Multiverse Thread Classification, Burak Sezi̇n Ovant, İsa Ahmet Güney, Muhammed Emi̇n Savaş, Gürhan Küçük
Last Level Cache Partitioning Via Multiverse Thread Classification, Burak Sezi̇n Ovant, İsa Ahmet Güney, Muhammed Emi̇n Savaş, Gürhan Küçük
Turkish Journal of Electrical Engineering and Computer Sciences
Last level caches (LLCs) are part of the last line of defense against the famous memory wall problem. Today, almost all processors utilize a LLC for the same reason. This study extends our previous work, which proposed a cache-partitioning mechanism using thread classification. Here, we propose three enhancements to the existing system: 1) an adaptive traffic threshold mechanism for more portable classification hardware, 2) a new method for classifying way-hungry threads, and finally, 3) a thorough comparison of two design alternatives. Compared to the original way- partitioning mechanism, we show that the proposed mechanism's performance improved by around 6%, on …
Usage Of Segmentation For Noise Elimination In Reconstructed Images In Digitalholographic Interferometry, Gülhan Ustabaş Kaya, Zehra Saraç
Usage Of Segmentation For Noise Elimination In Reconstructed Images In Digitalholographic Interferometry, Gülhan Ustabaş Kaya, Zehra Saraç
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, we propose to enhance the image in digital holography by using an artificial neural network and an iterative algorithm with Nakamura's approach based on segmentation. It is well known that reconstructed three- dimensional (3D) images suffer from noise in digital holography. In addition, obtaining 3D reconstructed images takes a long time due to large pixel numbers in reconstructed images and lack of memory in the system. The segmentation process is an application that overcomes these problems. Therefore, we focus on the implementation of segmentation for image enhancement. In addition, the results of the segmentation process for both …
Weighted Intensity Hue Saturation Transform For Image Enhancement Andpansharpening, Nur Hüseyi̇n Kaplan
Weighted Intensity Hue Saturation Transform For Image Enhancement Andpansharpening, Nur Hüseyi̇n Kaplan
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a weighted intensity hue saturation transform (WIHS) is proposed for image enhancement and pansharpening. The proposed transform obtains the intensity component of the classical intensity hue saturation (IHS) transform, by weighting the bands (red, green, and blue) of the image, whereas the hue and saturation components remain unchanged. The weight for each band is determined according to the brightness interval of the corresponding band and its standard deviation. The purpose of obtaining the intensity component by weighting is to keep more information from the bands of the input image. The classical intensity component used in image processing …
An Investigation On Characteristics Of Tracking Failure In Epoxy Resin Withharmonic And Fractal Dimension Analysis, Mehmet Murat İspi̇rli̇, Aysel Ersoy Yilmaz
An Investigation On Characteristics Of Tracking Failure In Epoxy Resin Withharmonic And Fractal Dimension Analysis, Mehmet Murat İspi̇rli̇, Aysel Ersoy Yilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
Epoxy resins have excellent mechanical and electrical properties; thus, they are commonly preferred in the electrical{electronic sector as insulation materials. These insulation materials experience degradation such as breakdown, tracking, or treeing. Therefore, safety and reliability tests of insulation materials have great importance in estimating the performance of insulation. These tests must be carried out to decrease the risk of electrical insulation fault. In this study, the relationship between tracking failures and the data obtained during experiments was evaluated. Tracking failure performance of epoxy resin was investigated using the IEC 60112 test standard, which is known as the comparative tracking index …
Outputs Bounds For Linear Systems With Repeated Input Signals: Existence,Computation And Application To Vehicle Platooning, Harun Buğra Sağlam, Klaus Werner Schmi̇dt
Outputs Bounds For Linear Systems With Repeated Input Signals: Existence,Computation And Application To Vehicle Platooning, Harun Buğra Sağlam, Klaus Werner Schmi̇dt
Turkish Journal of Electrical Engineering and Computer Sciences
This paper investigates the effect of repeated time-limited input signals on the output excursion of stable, linear time-invariant systems. It is first shown that the maximum norm of the output signal remains bounded if the repeated input signals are separated by a nonzero dwell time. Then a novel method for computing a tight bound on the output signal norm is proposed. The setting of the paper is motivated by a vehicle platooning application, where vehicles repeatedly open/close gaps in order to perform lane changes. The developed method analyzes driving safety by computing a bound on the spacing error between vehicles …
Model Reduction Of Discrete-Time Systems In Limited Intervals, Umair Zulfiqar, Muwahida Liaquat
Model Reduction Of Discrete-Time Systems In Limited Intervals, Umair Zulfiqar, Muwahida Liaquat
Turkish Journal of Electrical Engineering and Computer Sciences
Model order reduction (MOR) is a process of obtaining a lower order surrogate model that accurately approximates the original high-order system. Since no actuator or plant operates over the entire time and frequency ranges, the reduced-order model should be accurate in the actual range of operation. In this paper, model reduction techniques for discrete time systems are presented that ensure less reduction error in the specified time and frequency intervals. The techniques are tested on the benchmark numerical examples and their efficacy is shown.
Determination Of Harmonic Current Contributions Based On Robust State Estimation, Erhan Sezgi̇n, Murat Göl, Özgül Salor
Determination Of Harmonic Current Contributions Based On Robust State Estimation, Erhan Sezgi̇n, Murat Göl, Özgül Salor
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a state estimation based method is proposed to determine harmonic current contributions of plants supplied from a point of common coupling (PCC). This work mainly aims to reduce gross error of capacitive voltage transformer (CVT) measurements at harmonic frequencies using robust weighted least absolute value (WLAV) state estimation method, which provides the optimum state estimates for harmonic voltages in the presence of a redundant enough measurement set. Estimated harmonic voltages are then used to solve the harmonic current contribution problem based on superposition theorem. It has been shown that the proposed method can provide optimum harmonic estimates …
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Two-Area Load Frequency Control With Redox Ow Battery Using Intelligentalgorithms In A Restructured Scenario, Lakshmi Dhandapani, Fathima Peer, Ranganath Muthu
Turkish Journal of Electrical Engineering and Computer Sciences
Load frequency control (LFC) is an essential aspect of power system dynamics. This paper focuses on the optimization of LFC for a two-area deregulated power system under different scenarios. A recent nature-inspired ower pollination algorithm (FPA), based on the pollination process of plants, is used to tune the proportional integral (PI) controller parameters of LFC for the global minima solution. FPA is compared with a genetic algorithm, particle swarm optimization, and a conventional PI controller. During large load disturbance in the areas, controllers are incapable of reducing frequency deviations and tie-line power oscillations due to the slow response of the …
Signal Processing In Recursive Rejection Filters In The Transient Mode, Dmitrii Popov, Sergey Smolskiy
Signal Processing In Recursive Rejection Filters In The Transient Mode, Dmitrii Popov, Sergey Smolskiy
Turkish Journal of Electrical Engineering and Computer Sciences
A recursive rejection filter (REF) oriented to the radar signal extraction from the moving targets on a background of passive interference in the form of undesired re ections from fixed or slowly moving objects (so-called clutter) is the object under investigation. By means of the state variable method, which gives the adequate filter description in the time domain, the REF structure in the transient mode is synthesized, which is improved with the aim of transient acceleration with the clutter edge arriving. The REF structure's improvement in the transient mode is achieved by its reconfiguration, which is made by REF output …
Neural Network-Based Adaptive Tracking Control For A Nonholonomic Wheeledmobile Robot With Unknown Wheel Slips, Model Uncertainties, And Unknownbounded Disturbances, Tinh Nguyen, Linh Le
Neural Network-Based Adaptive Tracking Control For A Nonholonomic Wheeledmobile Robot With Unknown Wheel Slips, Model Uncertainties, And Unknownbounded Disturbances, Tinh Nguyen, Linh Le
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, an adaptive tracking controller based on a three-layer neural network (NN) with an online weight tuning algorithm is proposed for a nonholonomic wheeled mobile robot in the presence of unknown wheel slips, model uncertainties, and unknown bounded disturbances. The online weight tuning algorithm is modified from the backpropagation with an e-modification term required to assure that the NN weights are bounded. Preliminary neural network offline training is not essential for the weights. Thanks to this proposed controller, the desired tracking performance is achieved where position tracking errors converge to an arbitrarily small neighborhood of the origin regardless …