University of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Fabrication of Acetone Gas Sensor Based on Fe2O3 Decorated CNTs with Ag Interdigitated Electrodes on Al2O3 Substrate.Fabrication of Acetone Gas Sensor Based on Fe2O3 Decorated CNTs with Ag Interdigitated Electrodes on Al2O3 Substrate.3833901760010.22034/tjee.2024.54800.4570FAV.BabaeiDepartment of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, IranHamid RezaAnsariShiraz University of Technology, Shiraz, IranZ.KordrostamiResearch Centre for Design and Fabrication of Advanced Electronic Devices, Shiraz University of Technology, Shiraz, IranJournal Article20230104In this article, a resistive acetone gas sensor with high sensitivity is fabricated. A a two-stage thermal hydrolysis reaction has been used to synthesize the sensitive Carbon Nanotubes (CNTs) decorated with iron oxide nanoparticles (Fe2O3). Micro-scale silver Inter Digitated Electrodes (IDEs) made of silver have been deposited on alumina substrate which is resistant to high temperatures using optical lithography. The synthesis process includes functionalizing carbon nanotubes and then decorating them with iron oxide nanoparticles. The synthesized nanocomposite was characterized using X-ray diffraction and scanning electron microscopy. The results show that iron oxide nanoparticles uniformly decorated the surface of carbon nanotubes. The synthesized nanostructures were tested under different concentrations of acetone gas and showed appropriate response and high sensitivity. The fabricated sensor showed excellent selectivity, good reproducibility, and satisfactory response and recovery times. Decorating carbon nanotubes with iron oxide nanoparticles increases the sensitivity and speed of the sensor. The proposed sensor exposed to 100 ppm of acetone gas at a temperature of 300 degrees Celsius results in a resistance change of nearly 38 times. The improved sensor performance is mainly related to the material structure and the p-n junction between the CNTs and the iron oxide nanoparticles.In this article, a resistive acetone gas sensor with high sensitivity is fabricated. A a two-stage thermal hydrolysis reaction has been used to synthesize the sensitive Carbon Nanotubes (CNTs) decorated with iron oxide nanoparticles (Fe2O3). Micro-scale silver Inter Digitated Electrodes (IDEs) made of silver have been deposited on alumina substrate which is resistant to high temperatures using optical lithography. The synthesis process includes functionalizing carbon nanotubes and then decorating them with iron oxide nanoparticles. The synthesized nanocomposite was characterized using X-ray diffraction and scanning electron microscopy. The results show that iron oxide nanoparticles uniformly decorated the surface of carbon nanotubes. The synthesized nanostructures were tested under different concentrations of acetone gas and showed appropriate response and high sensitivity. The fabricated sensor showed excellent selectivity, good reproducibility, and satisfactory response and recovery times. Decorating carbon nanotubes with iron oxide nanoparticles increases the sensitivity and speed of the sensor. The proposed sensor exposed to 100 ppm of acetone gas at a temperature of 300 degrees Celsius results in a resistance change of nearly 38 times. The improved sensor performance is mainly related to the material structure and the p-n junction between the CNTs and the iron oxide nanoparticles.https://tjee.tabrizu.ac.ir/article_17600_3387d45bc3d82081b155de610d7e580e.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Long-term Visual Object Tracking of Arbitrary Objects Based on Switching Between Traditional Method and Deep Learning TechniqueLong-term Visual Object Tracking of Arbitrary Objects Based on Switching Between Traditional Method and Deep Learning Technique3914021766110.22034/tjee.2024.59362.4766FAM. A.BagherzadehFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranH.SeyedarabiFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranS. N.RazaviFaculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, IranJournal Article20231206Visual tracking of the arbitrary object is a fundamental and challenging topic in the field of machine vision, which has traditionally been done by considering a model for the target and using the training data of the same video. Most trackers can hardly top the results of the most popular methods when considering real-time and online performance. In this article, a tracker framework based on the Siamese network is presented, which is an online tracker learning and a real-time tracking process, and its name is STD-Siam. Since the Siamese network has limited online training and cannot handle the challenges of tracking for the long term, STD-Siam aims to switch between traditional tracking and deep learning, training both trackers to eliminate the ambiguity between the target and the background in each scenario. First, the training data is generated through the traditional tracker, then these data are expanded with the augmentation technique so that the deep network can be trained well. This method can be executed at a speed of 66 FPS, and compared to the current similar algorithms, despite its simplicity, it can achieve good results and track the target for the long term. This tracking speed is beyond real-time due to the spike detector in the frequency domain, which accurately calculates the selected target candidates and avoids blindly scanning the entire image to reduce the computational burden.Visual tracking of the arbitrary object is a fundamental and challenging topic in the field of machine vision, which has traditionally been done by considering a model for the target and using the training data of the same video. Most trackers can hardly top the results of the most popular methods when considering real-time and online performance. In this article, a tracker framework based on the Siamese network is presented, which is an online tracker learning and a real-time tracking process, and its name is STD-Siam. Since the Siamese network has limited online training and cannot handle the challenges of tracking for the long term, STD-Siam aims to switch between traditional tracking and deep learning, training both trackers to eliminate the ambiguity between the target and the background in each scenario. First, the training data is generated through the traditional tracker, then these data are expanded with the augmentation technique so that the deep network can be trained well. This method can be executed at a speed of 66 FPS, and compared to the current similar algorithms, despite its simplicity, it can achieve good results and track the target for the long term. This tracking speed is beyond real-time due to the spike detector in the frequency domain, which accurately calculates the selected target candidates and avoids blindly scanning the entire image to reduce the computational burden.https://tjee.tabrizu.ac.ir/article_17661_9240951fc61c48dd667450efb3b46b86.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Development of Tiny Machine Learning Models for Optimal Distribution of Workloads at Edge NetworksDevelopment of Tiny Machine Learning Models for Optimal Distribution of Workloads at Edge Networks4034121760110.22034/tjee.2024.57664.4672FAM.R.PourhosseinComputer Engineering Department, Engineering Faculty, Bu-Ali Sina University, Hamedan, Iran.M.AbbasiComputer Engineering Department, Engineering Faculty, Bu-Ali Sina University, Hamedan, Iran.E.Mohammadi-PasandComputer Engineering Department, Engineering Faculty, Bu-Ali Sina University, Hamedan, Iran.Journal Article20230820The number of devices connected to the Internet of Things has been expanded rapidly. This issue has caused a significant increase in the computational load in the networks. To overcome this challenge, cloud computing was presented as a suitable solution. However, cloud computing suffers significant delay to process workloads. Processing workloads at the edge of the network and locally leads to reduced latency. But due to the limitation of computing resources at the edge, managing and optimizing resources is considered one of the main challenges. Therefore, in addition to distributing the workloads at the edge of the network and maintaining the balance between energy consumption and delay, the limitation of resources such as memory consumption should be considered. In this paper, an online method based on XCS learning classifier systems (LCS), named TinyXCS, and an offline method based on decision tree, named TinyDT, are proposed to balance energy consumption and reduce delay in processing workloads considering the memory limitation at edge. The experimental results show the superiority of TinyXCS and TinyDT over similar methods. The simulation shows that in addition to workload distribution, the proposed methods can simultaneously reduce delay and energy consumption and create a compromise between them and memory consumption.The number of devices connected to the Internet of Things has been expanded rapidly. This issue has caused a significant increase in the computational load in the networks. To overcome this challenge, cloud computing was presented as a suitable solution. However, cloud computing suffers significant delay to process workloads. Processing workloads at the edge of the network and locally leads to reduced latency. But due to the limitation of computing resources at the edge, managing and optimizing resources is considered one of the main challenges. Therefore, in addition to distributing the workloads at the edge of the network and maintaining the balance between energy consumption and delay, the limitation of resources such as memory consumption should be considered. In this paper, an online method based on XCS learning classifier systems (LCS), named TinyXCS, and an offline method based on decision tree, named TinyDT, are proposed to balance energy consumption and reduce delay in processing workloads considering the memory limitation at edge. The experimental results show the superiority of TinyXCS and TinyDT over similar methods. The simulation shows that in addition to workload distribution, the proposed methods can simultaneously reduce delay and energy consumption and create a compromise between them and memory consumption.https://tjee.tabrizu.ac.ir/article_17601_4c526581ca606ba55a44d031cfbe5d3f.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Using generative adversarial networks to increase the classification efficiency of imbalanced user reviewsUsing generative adversarial networks to increase the classification efficiency of imbalanced user reviews4134221754110.22034/tjee.2024.58494.4724FAB.JavidFaculty of Computer Engineering, Shahrood University of Technology, Shahrood, IranH.MashayekhiFaculty of Computer Engineering, Shahrood University of Technology, Shahrood, IranJournal Article20230918Text generation methods use artificial intelligence to automatically generate natural language texts. One of the uses of text generation is in text classification. Many real-world problems are related to imbalanced textual data, which can reduce classification efficiency. One approach to solving the imbalanced data problem is the minority class oversampling. Due to the progress of generative adversarial networks (GAN) in data generation, these networks can be used to generate text samples in oversampling. Generating text using GANs is a complex problem due to the discrete nature of text. Despite their potential, the use of these networks in solving the problem of imbalanced textual data has rarely been investigated. This article examines the effect of using the SentiGAN network to solve the problem of imbalanced user reviews with the aim of improving the classification efficiency. To evaluate the proposed method, before and after oversampling with traditional, recent and SentiGAN methods, four classification algorithms were implemented on the data and evaluation criteria were calculated. It was observed that oversampling with the help of SentiGAN has increased the accuracy, precision, specificity and f_score of zero class compared to the situation where the data is imbalanced or even is oversampled by the other methods.Text generation methods use artificial intelligence to automatically generate natural language texts. One of the uses of text generation is in text classification. Many real-world problems are related to imbalanced textual data, which can reduce classification efficiency. One approach to solving the imbalanced data problem is the minority class oversampling. Due to the progress of generative adversarial networks (GAN) in data generation, these networks can be used to generate text samples in oversampling. Generating text using GANs is a complex problem due to the discrete nature of text. Despite their potential, the use of these networks in solving the problem of imbalanced textual data has rarely been investigated. This article examines the effect of using the SentiGAN network to solve the problem of imbalanced user reviews with the aim of improving the classification efficiency. To evaluate the proposed method, before and after oversampling with traditional, recent and SentiGAN methods, four classification algorithms were implemented on the data and evaluation criteria were calculated. It was observed that oversampling with the help of SentiGAN has increased the accuracy, precision, specificity and f_score of zero class compared to the situation where the data is imbalanced or even is oversampled by the other methods.https://tjee.tabrizu.ac.ir/article_17541_ec91a79925d632878626cea8d4ce39dd.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121A Bi-level Model for Low Voltage Distribution Network Planning Simultaneously with the Voltage Stability of Medium Voltage NetworkA Bi-level Model for Low Voltage Distribution Network Planning Simultaneously with the Voltage Stability of Medium Voltage Network4234321766010.22034/tjee.2024.58402.4720FAA.RastgouDepartment of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, IranS.Hosseini-HematiDepartment of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, IranJournal Article20230912In this paper, a model for distribution network expansion planning is presented, which is based on a bi-level model and can resolve the conflict between the medium and low voltage distribution networks in the size and optimal placement of transformers. In the proposed model, the upper and lower levels are medium and low voltage networks, respectively. The conflict between the two levels is that each network tends to determine the location and size of the transformers according to their wishes. Therefore, this paper has tried to solve this conflict, which is the size and location of transformers, by presenting a bi-level model, and to reach an optimal point that is in accordance with the desire of both levels. The objective function of the first level is the voltage stability criterion and the objective function of the second level is to reduce the operating and investment costs by considering distributed generations. Since the desired model is non-linear, it is solved using the tabu search by splitting the model into two sub-problems. To show the effectiveness of the proposed model, the problem is solved in three different scenarios and necessary comparisons have been made.In this paper, a model for distribution network expansion planning is presented, which is based on a bi-level model and can resolve the conflict between the medium and low voltage distribution networks in the size and optimal placement of transformers. In the proposed model, the upper and lower levels are medium and low voltage networks, respectively. The conflict between the two levels is that each network tends to determine the location and size of the transformers according to their wishes. Therefore, this paper has tried to solve this conflict, which is the size and location of transformers, by presenting a bi-level model, and to reach an optimal point that is in accordance with the desire of both levels. The objective function of the first level is the voltage stability criterion and the objective function of the second level is to reduce the operating and investment costs by considering distributed generations. Since the desired model is non-linear, it is solved using the tabu search by splitting the model into two sub-problems. To show the effectiveness of the proposed model, the problem is solved in three different scenarios and necessary comparisons have been made.https://tjee.tabrizu.ac.ir/article_17660_5673d9e99f19fbf1b4fe72587a3880b5.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Real-time Control and Management of a Microgrid, with Dispersed Generation Resources, Utilizing a Integrated Proton Exchange Membrane Fuel Cell ModelReal-time Control and Management of a Microgrid, with Dispersed Generation Resources, Utilizing a Integrated Proton Exchange Membrane Fuel Cell Model4334441765610.22034/tjee.2024.58080.4696FAS.RoudnilElectrical and Computer Engineering Faculty - Power Department, University of Tabriz, Tabriz, Iran.S.Ghassem ZadehElectrical and Computer Engineering Faculty - Power Department, University of Tabriz, Tabriz, Iran.Journal Article20230823In this paper, a real-time control method is proposed for the energy management of a grid-connected microgrid including fuel cell, photovoltaic panels (PV) as distributed energy resources (DERs), and battery as energy storage system (ESS). The control method is based on model predictive control (MPC) and optimized using the particle swarm optimization (PSO) algorithm. By modeling the control method, predictive data obtained from simulating microgrid performance at each instance are utilized. Real-time microgrid control is then performed by combining these predicted data with real-time measurements. The purpose of this control method is to achieve integrated management of the microgrid and reduce changes in the battery’s state of charge (SoC) and fuel cell’s level of hydrogen (LoH). This reduction helps minimize excessive usage of the battery and fuel cell, thus reducing their depreciation. Moreover, the proposed control method enables PV and fuel cell to supply most of the required demand, with excess electric power being sold to the main grid. Additionally, the battery functions to absorbs power fluctuations, as demonstrated in the simulation results investigating these objectives.In this paper, a real-time control method is proposed for the energy management of a grid-connected microgrid including fuel cell, photovoltaic panels (PV) as distributed energy resources (DERs), and battery as energy storage system (ESS). The control method is based on model predictive control (MPC) and optimized using the particle swarm optimization (PSO) algorithm. By modeling the control method, predictive data obtained from simulating microgrid performance at each instance are utilized. Real-time microgrid control is then performed by combining these predicted data with real-time measurements. The purpose of this control method is to achieve integrated management of the microgrid and reduce changes in the battery’s state of charge (SoC) and fuel cell’s level of hydrogen (LoH). This reduction helps minimize excessive usage of the battery and fuel cell, thus reducing their depreciation. Moreover, the proposed control method enables PV and fuel cell to supply most of the required demand, with excess electric power being sold to the main grid. Additionally, the battery functions to absorbs power fluctuations, as demonstrated in the simulation results investigating these objectives.https://tjee.tabrizu.ac.ir/article_17656_7cd451a9c120ae350502e7147810c81c.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121A Spin Hall Effect-Based Dual Mode Nonvolatile Flip-Flop for Realizing Nonvolatile ComputingA Spin Hall Effect-Based Dual Mode Nonvolatile Flip-Flop for Realizing Nonvolatile Computing4454541766210.22034/tjee.2024.59390.4768FAS.MofidiDepartment of Computer Engineering, Shahid Bahonar University of Kerman (SBUK), Kerman, IranJournal Article20231129In computing circuits, when the voltage source is suddenly cut off, data is lost and calculations need to be performed again. This reduces the speed of calculations and increases power consumption. This issue becomes more important in applications that are powered by batteries such as "Internet of Things". Recently, the use of non-volatile flip-flops in computing circuits has received much attention. In non-volatile circuits that have been proposed so far, a separate backup circuit based on a non-volatile flip-flop is used. This circuit performs data storage on the chip at specific time intervals. But the use of a separate backup circuit ultimately leads to an increase in the total power consumption, the occupied area, and a decrease in the calculation speed. In addition, the backup circuit requires external control signals, which results in increasing the complexity of the system. To solve these problems, in this paper, a double mode non-volatile flip-flop with both simultaneous and asynchronous backup of data is proposed, in which mCell devices are used to realize non-volatile calculations. The proposed flip-flop for backup and recovery operations, has the energy of fJ level and the delay of ps level.In computing circuits, when the voltage source is suddenly cut off, data is lost and calculations need to be performed again. This reduces the speed of calculations and increases power consumption. This issue becomes more important in applications that are powered by batteries such as "Internet of Things". Recently, the use of non-volatile flip-flops in computing circuits has received much attention. In non-volatile circuits that have been proposed so far, a separate backup circuit based on a non-volatile flip-flop is used. This circuit performs data storage on the chip at specific time intervals. But the use of a separate backup circuit ultimately leads to an increase in the total power consumption, the occupied area, and a decrease in the calculation speed. In addition, the backup circuit requires external control signals, which results in increasing the complexity of the system. To solve these problems, in this paper, a double mode non-volatile flip-flop with both simultaneous and asynchronous backup of data is proposed, in which mCell devices are used to realize non-volatile calculations. The proposed flip-flop for backup and recovery operations, has the energy of fJ level and the delay of ps level.https://tjee.tabrizu.ac.ir/article_17662_63b1d7631321d86cf9c1eeaaba87eaae.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Design and Implementation of a DC- 18 GHz Microwave Triplexer in Suspended Stripline TechnologyDesign and Implementation of a DC- 18 GHz Microwave Triplexer in Suspended Stripline Technology4554641760210.22034/tjee.2024.58972.4751FAS. M.MiriSchool of Electrical and Computer Engineering, University of Tehran, Tehran, Iran. 2 School of Electrical and Computer Engineering,K.Mohammadpour AghdamSchool of Electrical and Computer Engineering, Shiraz University, Shiraz, IranS.O.MiriSchool of Electrical and Computer Engineering, Shiraz University, Shiraz, IranJournal Article20231025This paper presents design, optimization and measurement results of a microwave triplexer implemented using suspended stripline technology to separate DC-18 GHz input signal into three jointed frequency ranges of DC-2 GHz, 2-6 GHz and 6-18 GHz with VSWR better than 2, isolation higher than 50 dB and insertion loss better than 1 dB. The proposed triplexer consists of lowpass and pseudo-highpass filter channels connected by suitable high and low impedance T-junctions. These filters are realized using generalized Chebyshev lowpass prototype to achieve high selectivity and sharp band-edge roll-off with ease in implementation by using printed circuit board technology. Stepped impedance resonators are used to achieve a better impedance matching and wideband response. The triplexer pattern is implemented on a 0.254 mm-thick RT/duroid 5880 substrate with dielectric constant of 2.2, suspended symmetrically between two ground planes which enables the realization of a contiguous triplexer with low insertion loss, high selectivity and high isolation. This Triplexer can be used in Radar warning receivers and electronic intelligent systems.This paper presents design, optimization and measurement results of a microwave triplexer implemented using suspended stripline technology to separate DC-18 GHz input signal into three jointed frequency ranges of DC-2 GHz, 2-6 GHz and 6-18 GHz with VSWR better than 2, isolation higher than 50 dB and insertion loss better than 1 dB. The proposed triplexer consists of lowpass and pseudo-highpass filter channels connected by suitable high and low impedance T-junctions. These filters are realized using generalized Chebyshev lowpass prototype to achieve high selectivity and sharp band-edge roll-off with ease in implementation by using printed circuit board technology. Stepped impedance resonators are used to achieve a better impedance matching and wideband response. The triplexer pattern is implemented on a 0.254 mm-thick RT/duroid 5880 substrate with dielectric constant of 2.2, suspended symmetrically between two ground planes which enables the realization of a contiguous triplexer with low insertion loss, high selectivity and high isolation. This Triplexer can be used in Radar warning receivers and electronic intelligent systems.https://tjee.tabrizu.ac.ir/article_17602_b680f674fce0be0a5ab6cf78904b3a6a.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Generating all compact codes with constraint on the smallest codelengthGenerating all compact codes with constraint on the smallest codelength4654761760310.22034/tjee.2024.58987.4752FAH.NarimaniDepartment of electrical and computer engineering, Isfahan University of Technology, Isfahan, IranM.KhosravifardDepartment of electrical and computer engineering, Isfahan University of Technology, Isfahan, IranJournal Article20231025Although by employing the Huffman algorithm one can construct the compact code (code with Kraft sum equal to 1) with minimum redundancy for an information source, in some problems it is required to first construct all possible compact codes and then select an appropriate one on the basis of a desired criterion. In particular, if the length of all codewords of an n-tuple compact code is λ or more, then the difference between the largest and the smallest codeword lengths is limited to n-2^λ, and as a result, by considering larger values for λ, the variation in delay of decoding different symbols of the source can be reduced. The main goal of this paper is construction of all such codes and an algorithm is introduced which generates only these codes (i.e., n-tuple compact codes with all codewords of length λ or more). Noting the correspondence between the multiplicity vectors of the compact codes and some sequences of numbers, we find the necessary and sufficient condition that a sequence of numbers is correspondent with a compact code with the shortest codeword at least λ bits long. This way by generating all suitable sequences, all the desired compact codes can be constructed without generating any other compact code. Using the proposed algorithm, less computational resources are required. For example, for λ=3, the required computational resources for generating only the desired compact codes are 5 percent of those when all compact codes are generated.Although by employing the Huffman algorithm one can construct the compact code (code with Kraft sum equal to 1) with minimum redundancy for an information source, in some problems it is required to first construct all possible compact codes and then select an appropriate one on the basis of a desired criterion. In particular, if the length of all codewords of an n-tuple compact code is λ or more, then the difference between the largest and the smallest codeword lengths is limited to n-2^λ, and as a result, by considering larger values for λ, the variation in delay of decoding different symbols of the source can be reduced. The main goal of this paper is construction of all such codes and an algorithm is introduced which generates only these codes (i.e., n-tuple compact codes with all codewords of length λ or more). Noting the correspondence between the multiplicity vectors of the compact codes and some sequences of numbers, we find the necessary and sufficient condition that a sequence of numbers is correspondent with a compact code with the shortest codeword at least λ bits long. This way by generating all suitable sequences, all the desired compact codes can be constructed without generating any other compact code. Using the proposed algorithm, less computational resources are required. For example, for λ=3, the required computational resources for generating only the desired compact codes are 5 percent of those when all compact codes are generated.https://tjee.tabrizu.ac.ir/article_17603_139208c0f77d0d2ae297351d0d77a234.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121Using disturbance estimator in a model predictive control for single-phase current source rectifiersUsing disturbance estimator in a model predictive control for single-phase current source rectifiers4774851754210.22034/tjee.2024.58842.4739FAA.HassanniaUniversity of Sistan and BaluchestanS. MasoudBarakatiUniversity of Sistan and BaluchestanS.H.TorabiUniversity of Sistan and BaluchestanJournal Article20231015In this paper, first a model predictive control (MPC) for a single-phase current source rectifier (CSR) is developed used in electric vehicle (EV) charger structures. Due to the uncertainties in its model caused by varying points of connection to the power grid, a disturbance estimator is necessary. In addition to the uncertainties, the CSR model's precision is diminished by the rectifier output's unmodeled dynamics. The disturbance estimator with Lagrange extrapolation yields a more precise model of the single-phase CSR for MPC. Finite control set model predictive control (FCS-MPC) is used to minimize switching losses by providing an optimal control input, eliminating the need for a modulator due to the limited number of permissible switching modes. The proposed control method is simulated in MATLAB software and implemented on a 4-kW laboratory prototype. Simulation and experimental results confirm the validity of the proposed control method.In this paper, first a model predictive control (MPC) for a single-phase current source rectifier (CSR) is developed used in electric vehicle (EV) charger structures. Due to the uncertainties in its model caused by varying points of connection to the power grid, a disturbance estimator is necessary. In addition to the uncertainties, the CSR model's precision is diminished by the rectifier output's unmodeled dynamics. The disturbance estimator with Lagrange extrapolation yields a more precise model of the single-phase CSR for MPC. Finite control set model predictive control (FCS-MPC) is used to minimize switching losses by providing an optimal control input, eliminating the need for a modulator due to the limited number of permissible switching modes. The proposed control method is simulated in MATLAB software and implemented on a 4-kW laboratory prototype. Simulation and experimental results confirm the validity of the proposed control method.https://tjee.tabrizu.ac.ir/article_17542_7435a1cfb93347e75914468cd376f979.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121An Efficient Metasurface-Based Wireless Power Transfer System for Implantable Medical DevicesAn Efficient Metasurface-Based Wireless Power Transfer System for Implantable Medical Devices4874941765910.22034/tjee.2024.57636.4671FAS. A.HosseiniFaculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran.M.YazdiFaculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran.Journal Article20230721In this paper, by designing a double metasurface, an efficient wireless power transfer system is proposed for implementable medical applications. This system operates at 2.45 GHz in the medical frequency band and consists of two antennas, a transmitter, and a receiver, along with a double metasurface structure embedded between them. A circular patch antenna for the transmitting end and a small loop antenna on the receiving side are designed. To enhance the efficiency of the system, a double metasurface consisting of two arrays of hexagonal ring unit cells is located between the receiver and transmitter antennas. As the receiver antenna is designed for operation in a human body medium, the effects of antenna displacement as well as material uncertainty on the efficiency of total structure are investigated in which reasonable stability concerning these variations is observed. Finally, as this system is aimed to operate in the human body, the safety of this system has also been approved through the calculation of the specific absorption rate (SAR). The proposed wireless power transfer system can overcome the challenges of using implementable medical electronic devices such as battery-replacing surgeries.In this paper, by designing a double metasurface, an efficient wireless power transfer system is proposed for implementable medical applications. This system operates at 2.45 GHz in the medical frequency band and consists of two antennas, a transmitter, and a receiver, along with a double metasurface structure embedded between them. A circular patch antenna for the transmitting end and a small loop antenna on the receiving side are designed. To enhance the efficiency of the system, a double metasurface consisting of two arrays of hexagonal ring unit cells is located between the receiver and transmitter antennas. As the receiver antenna is designed for operation in a human body medium, the effects of antenna displacement as well as material uncertainty on the efficiency of total structure are investigated in which reasonable stability concerning these variations is observed. Finally, as this system is aimed to operate in the human body, the safety of this system has also been approved through the calculation of the specific absorption rate (SAR). The proposed wireless power transfer system can overcome the challenges of using implementable medical electronic devices such as battery-replacing surgeries.https://tjee.tabrizu.ac.ir/article_17659_804813330c8da3d33bb9f0ca000cfde0.pdfUniversity of TabrizTabriz Journal of Electrical Engineering2008-779954420241121High Performance Hybrid Robust Extended Kalman Filter Design with Application to Large MisalignmentsHigh Performance Hybrid Robust Extended Kalman Filter Design with Application to Large Misalignments4955041732710.22034/tjee.2023.57843.4683FAFatemehRahemiSahand University of Technology, Faculty of Electrical Engineering, Tabriz, IRANMohammad JavadKhosrowjerdiFaculty of Electrical Engineering, Sahand University of Technology, Sahand, Tabriz, Iran.AhmadAkbariSahand University of Technology, Faculty of Electrical Engineering, Tabriz, IRANSaeedEbadollahiElectrical Engineering, Department of Electrical Engineering, Iran University of Science and Technology, Tehran, IranJournal Article20230820In many applications, especially military applications, the inertial navigation system (INS) needs to achieve a high level of accuracy in a short time. For alignment, recursive estimator filters and, in non-linear cases, the Extended Kalman Filter (EKF) is often used. The dynamics of a real, continuous system and the output of the sensors are available discretely. Therefore, a hybrid filter has been used. In addition, a robust filter is used to increase the reliability of system operation. In this paper, a Hybrid Extended Kalman Filter (HEKF) is presented and then upgraded to the Hybrid Robust Extended Kalman Filter (HREKF). By running the algorithm on the data of a real system, it was observed that the speed of convergence increased especially in the yaw direction. By running the algorithm on the data of a real system, it was observed that the speed of convergence has increased especially in the yaw direction. Finally, using the impulsive system approach, a new stability analysis of the proposed algorithms is presented, which guarantees the boundedness of the error estimation, which is unique.In many applications, especially military applications, the inertial navigation system (INS) needs to achieve a high level of accuracy in a short time. For alignment, recursive estimator filters and, in non-linear cases, the Extended Kalman Filter (EKF) is often used. The dynamics of a real, continuous system and the output of the sensors are available discretely. Therefore, a hybrid filter has been used. In addition, a robust filter is used to increase the reliability of system operation. In this paper, a Hybrid Extended Kalman Filter (HEKF) is presented and then upgraded to the Hybrid Robust Extended Kalman Filter (HREKF). By running the algorithm on the data of a real system, it was observed that the speed of convergence increased especially in the yaw direction. By running the algorithm on the data of a real system, it was observed that the speed of convergence has increased especially in the yaw direction. Finally, using the impulsive system approach, a new stability analysis of the proposed algorithms is presented, which guarantees the boundedness of the error estimation, which is unique.https://tjee.tabrizu.ac.ir/article_17327_9b69d9f02fc4e950caf250eafc140102.pdf