Showing 456 results for Ha
Masoud Hashemi, Mohsen Kalantar,
Volume 21, Issue 4 (December 2025)
Abstract
The basis of the extensive measurement systems is based on the placement of phasor measurement units (PMUs) in the power grids. With the ever increasing expansion of electric energy consumption and the emergence of the phenomenon of restructuring in power grids and the existence of problems such as extensive blackouts of the power grid has increased the desire of power grid operators to use a wide area monitoring system (WAMS). This paper discusses the problem of optimal placement of phasor measurement units (PMUs) in power grids, which is a critical issue for the reliable and safe operation of power systems. We proposed a multi-objective binary optimization algorithm called the Multi-Objective Binary Harris Hawks Optimization algorithm based on Region selection (MOBHHO/R) to solve this problem. One of the most important innovations of the proposed algorithm is to draw inspiration from feature called a repository or archive to store optimal responses at each stage of the simulation. The algorithm aims to minimize the number of PMUs required while maximizing the observability of the power grids. The proposed algorithm is implemented on the standard IEEE 14 and 30 bus power systems, and the results show its superiority compared to other algorithms.
Mahendra Shridhar Naik, Chaitra S N, Amit Kumar K,
Volume 21, Issue 4 (December 2025)
Abstract
6LoWPAN is a significant innovation for low-power devices such as sensors and motes, enabling efficient communication in IoT networks. This paper examines the impact of topology and sink node placement on data delivery within these networks, focusing on the Routing Protocol for Low-Power and Lossy Networks (RPL). Various network performance metrics are evaluated to determine optimal routing paths, revealing that increased node density and network size lead to higher delays and congestion. The study highlights that the central placement of the sink node enhances performance. Comparatively, mesh topology outperforms random topology in terms of efficiency. Simulations were conducted to evaluate the effectiveness of Objective Functions (OFs), specifically OF0 and MRHOF. The results indicate that MRHOF surpasses OF0, with performance improvements scaling with network size.
Majid Golkhatab, Aref Shahmansoorian, Mohsen Davoudi,
Volume 21, Issue 4 (December 2025)
Abstract
This paper presents a novel hybrid navigation approach for autonomous mobile robots in obstacle-rich environments. The method integrates artificial potential fields for obstacle avoidance with fuzzy logic for path planning, which is optimized by a genetic algorithm to enhance adaptability and robustness to sensor uncertainties. Experimental results demonstrate significant improvements over traditional artificial potential field methods and are validated through real-time implementation on a ROS-based mobile robot.
Suhail Mahmoud Abdullah, Thamir Hassan Atyia,
Volume 21, Issue 4 (December 2025)
Abstract
Optimal control of DC motors remains a critical research area in modern control systems, given their wide industrial applications and the need for accurate performance under variable conditions. This paper explores the application of genetic algorithms (GAs) to optimize the control parameters of DC motors, particularly PID controllers, with the goal of improving the dynamic response and robustness of DC motor systems. Compared to traditional constraint-based tuning methods, GAs, inspired by natural selection and evolution, offer comprehensive search capabilities that significantly improve parameter optimization, providing better speed regulation, reduced overshoot, and minimal steady-state error. This review highlights the key challenges faced when using GAs. Comparative results from various studies demonstrate that GA-based controllers consistently outperform traditional tuning methods in terms of stability, efficiency, and adaptability. Key findings related to energy consumption and stability are highlighted. It is essential to analyze the system performance in terms of rise time (tr), settling time (ts), overshoot ratio (Mp%), and steady-state error (Ess). A proportional-integral-differential (PID) controller provides a stable response by tuning its parameters according to a specific methodology using a genetic algorithm. This paper concludes by emphasizing the potential of genetic generators as a powerful and flexible optimization tool for intelligent control of DC motors.
Omar S Abdulwahid, Saad G Muttlak, James Sexton, Michael J Kelly, Mohamed Missous,
Volume 21, Issue 4 (December 2025)
Abstract
An analysis of 6×6 µm2 GaAs/AlAs Asymmetric Spacer Layer Tunnel diode has been conducted to evaluate the DC and RF characteristics at different bias conditions. At zero voltage operation, the diode exhibited a measured curvature coefficient of 22 V-1, corresponding to a junction resistance of 27 kΩ. The measured and simulated S11 reflection coefficient of the integrated detector including the diode, matching circuit, and output capacitance achieved to be less than -10 dB at the desired frequency. The extracted low series resistance and junction capacitance of the tunnel diode resulted a high voltage sensitivity of 3650 V/W and low noise equivalent power of 5.5 pW/
at 11 GHz resonant frequency and -27 dBm input power. The developed detector model can be extended to implement RF detectors operating at frequencies reaching mm-wave regime applications. This is with consideration of the requirements for sub-micrometer scale mesa devices, eliminating the effects of associated parasitic elements and improved matching network performance.
Hamid Reza Sezavar, Saeed Hasanzadeh,
Volume 21, Issue 4 (December 2025)
Abstract
Marx generators that produce output pulses in the range of a few kilovolts (kV) with energies of a few millijoules (mJ) and rise times of a few nanoseconds (ns) have a variety of applications, including enhancing hydrogen production through electrolysis. In these generators, bipolar junction transistors (BJTs) operating in avalanche breakdown mode are employed as switches. This study explores the use of transistors specifically designed for avalanche breakdown to improve hydrogen generation efficiency from renewable energy sources. For this purpose, the FMMT415 transistor was implemented in the generator. The designed circuit was simulated with the transistors in avalanche breakdown mode, and the effects of various parameters on the output voltage were examined, particularly in the context of optimizing electrolysis performance. Based on the simulation results, the circuit was constructed and tested, and the differences in transistor parameters were evaluated. The simulation outcomes were then compared with the actual results. From these investigations, criteria were developed to determine the parameters that ensure suitable output voltage for Marx generator applications in hydrogen production. The optimal number of stages for the Marx generator was estimated based on the findings, highlighting its potential role in advancing sustainable hydrogen energy systems.
Mohammad Reza Eesazadeh, Zahra Nasiri-Gheidari,
Volume 21, Issue 4 (December 2025)
Abstract
This research focuses on electromagnetic position sensors, particularly synchros, which play a crucial role in the closed-loop control systems of permanent magnet synchronous machines (PMSMs). Compared to two-phase resolvers, three-phase synchros provide enhanced reliability by ensuring continued operation even in the event of an open-circuit fault. One of the key challenges in designing such sensors lies in selecting optimal windings and configurations while also developing efficient modeling techniques to minimize computational complexity. To address this issue, the study introduces a matrix-based method for designing wound rotor (WR) synchros. This approach allows for flexible configurations depending on the number of pole pairs and stator tooth counts. The proposed design methodology ensures adaptability and precision, making it a valuable tool for engineers working on electromagnetic sensor development. To validate the effectiveness of the proposed method, the Field Reconstruction Method (FRM) is employed, providing a fast and accurate modeling technique that can be implemented using MATLAB. Additionally, a comparative analysis is conducted with finite element analysis (FEA) to confirm the accuracy and reliability of the approach. Results demonstrate that the matrix-based method is an efficient and effective solution for optimizing WR synchro designs, significantly improving performance and computational efficiency.
Bhagyashree Ingle, Milind Nemade,
Volume 22, Issue 0 (In Press 2026)
Abstract
Computing paradigm has perceived a logical shift from CPU towards application specific GPU, FPGA, CPLD due to slow down of Moore’s Law, operating system overheads, serial data processing, memory management, power efficiency and speed. The performance increase of general-purpose CPUs & GPUs is unable to match with the advances in peripheral interfaces, reconfigurable logic deployed in FPGAs provides several exceptional properties that may be able to deliver desired performance. FPGA based digital circuits provide an intermediate arrangement between ASIC and CPU with regards to through-put, latency, portability and design time. True random number generators (TRNG) are expensive, low bandwidth and speed, non-compatible with FPGA or heterogenous architectures. Therefore, design and development of alternative and affordable random-number generators is focused by several researchers. TRNG design in FPGAs is more challenging because it must meet low power and area, high speed and throughput requirements without comprising the statistical quality of the desired results for intended applications. In this paper, an attempt has been made to highlight emerging techniques and challenges associated with FPGA implementation of random number generator. Furthermore, forthcoming techniques with the use of heterogeneous computation using FPGA and python productive multiprocessor system on chip (MPSoC) architecture for generation of random numbers are discussed.
Mostafa Madanchi Zaj, seyed Ahmadreza Afsari Kashani,
Volume 22, Issue 0 (In Press 2026)
Abstract
Rare-earth permanent magnet (PM) devices are increasingly facing challenges due to market monopolies. To mitigate these concerns, researchers have focused on reducing the use of rare-earth PMs while maintaining device performance. This study presents a novel hybrid structure for coaxial magnetic gears, combining the benefits of both magnetic and reluctance-based models. The proposed configuration delivers effective torque, reduced losses, and reliable performance at high speeds, all while minimizing magnet volume. The hybrid approach enhances high-speed performance, decreases the reliance on rare-earth magnets, and improves overall efficiency by incorporating reluctance principles into the inner rotor. In addition to new rotor section designs, three alternative hybrid rotor configurations are proposed. Particle Swarm Optimization algorithm is applied for optimization. ANSYS Maxwell and OptiSLang are used for electromagnetic simulation and optimization, and ANSYS Workbench is employed to assess mechanical performance. Unlike previously reported hybrid magnetic gears that rely solely on permanent-magnet-based torque production, the proposed topology combines permanent-magnet excitation and reluctance-based permeance modulation within a unified coaxial magnetic gear architecture.
M. J. Jahantab, S. Tohidi, Mohammad Reza Mosavi, Diego Martín de Andrés,
Volume 22, Issue 0 (In Press 2026)
Abstract
Global Positioning System (GPS) spoofing poses serious threats to navigation systems, as it transmits false GPS signals that cause receivers to compute incorrect positions. To address this issue, our research in this study focused on leveraging the Cross-Ambiguity Function (CAF) along with advanced machine learning techniques to effectively detect spoofing attacks. A further challenge in using CAF for spoofing detection is its high dimensionality, which demands powerful hardware and considerably slows down the detection process. Detecting spoofing signals with delays of less than 0.5 chips relative to the authentic signal is particularly difficult. To overcome this, the SVD_Var dimensionality reduction algorithm, which leverages the variance of CAF data through Singular Value Decomposition (SVD), is proposed to enhance both speed and detection performance. The reduced-dimensionality data are subsequently used to train a basic Multi-Layer Perceptron (MLP) neural network and the k-Nearest Neighbors (kNN) algorithm. The effectiveness of the proposed method is validated using the widely recognized Texas Spoofing Test Battery (TEXBAT) dataset. Results indicate that the method achieves an average detection rate exceeding 80% across various TEXBAT scenarios, demonstrating enhanced sensitivity and robustness in spoofing detection compared to both traditional and state-of-the-art approaches. Also, this approach accomplishes a dimensionality reduction ranging from 99.69% to 99.99% in terms of the number of pixels which significantly accelerates the processing speed.
N. Dabaghi Daryan, Mohammad Reza Mosavi, Sattar Mirzakuchaki, S. Tohidi,
Volume 22, Issue 0 (In Press 2026)
Abstract
GNSS simulators are essential tools for testing and validating satellite navigation system receivers across various civil applications. This study introduces an improved GLONASS satellite simulator to optimize navigation precision by enhancing the satellite constellation's Dilution of Precision (DOP). The proposed simulator operates in two steps. In the first step, the system performs a full-day search to identify time intervals with minimal DOP using a local moving-average technique. In the second step, the impact of adding one virtual satellite—selected using fuzzy logic and evaluated through the Residual Geometric Dilution of Precision (RGDOP) metric—is examined to minimize Geometric Dilution of Precision (GDOP). The fuzzy system uses two inputs (RGDOP and elevation angle), where RGDOP is modeled with four Gaussian membership functions (very small, small, medium, large), and the elevation angle is modeled with three triangular membership functions (small, medium, large). These scenarios are tested on a Software-Defined Radio (SDR) and then a u‑blox M8 receiver to evaluate and compare improvements in positioning accuracy across the tuned configurations. The results show that both optimization stages lead to significant gains in navigation performance. The first scenario leads to a 24.4% improvement in accuracy, while the second scenario achieves an even greater enhancement of 54.9%, highlighting the effectiveness of these approaches in reducing positioning error.
Seyed Moein Mortezaie, Mohammad Sarvi,
Volume 22, Issue 0 (In Press 2026)
Abstract
This paper proposes a transformerless, non-isolated high-gain DC–DC conversion stage intended for interfacing photovoltaic (PV) sources. The topology uses a hybrid leg arrangement in which inductor-based switching cells are combined with a symmetrically arranged capacitor switching network forming three identical branches. These branches share the input power and collectively provide a large step-up ratio while maintaining balanced branch currents. The converter operates with continuously flowing inductor currents, and an analytical model is developed to obtain closed-form relations for voltage gain, semiconductor stresses, and design equations for the main passive components. Guidelines are provided for selecting inductors, capacitors, and device ratings under ripple constraints, resonant concerns, and safe operating limits. To validate the analysis, a 250-W implementation is examined using a detailed switching model in MATLAB/Simulink. The results show stable steady-state waveforms over a broad range of duty-cycle combinations and indicate that semiconductor voltage stress remains well below the output level, enabling the use of fast, low-voltage-rated switches and yielding good efficiency. The dual-duty modulation strategy improves adaptability to variations in PV irradiance and load by allowing flexible gain control through coordinated adjustment of duty cycles.
Sudipta Chatterjee, Angshuman Majumdar, Arighna Basak, Amitesh Das, Vertika Rai,
Volume 22, Issue 1 (March 2026)
Abstract
This paper offers a comprehensive examination of smart robotic wheelchairs and their role in enhancing the mobility and independence of individuals with disabilities. Conventional wheelchairs often restrict users, leading to limited movement and accessibility. The emergence of smart robotic wheelchairs presents a promising solution to these issues. The study provides an overview of wheelchair technology, highlights challenges faced by individuals with disabilities, and assesses the benefits and drawbacks of smart robotic wheelchairs through a review of previous research. It delves into the features and functionalities of these wheelchairs, such as navigation and obstacle avoidance, autonomous and semi-autonomous modes, and customizable control options. Additionally, it analyses user experience, performance evaluation, and the impact on mobility and independence. The paper concludes by outlining future research directions and recommendations to further empower individuals with disabilities and enhance their quality of life.
Arun Pratap Singh Rathod, Pawan Kumar Mishra, Abhilasha Mishra,
Volume 22, Issue 1 (March 2026)
Abstract
In recent years, organic field effect transistors, also known as OFETs, have witnessed a substantial demand, mainly due to their expanding applications in the display and sensor industries, owing to simple fabrication techniques and cost-effective raw materials. But due to limited charge mobility, its applications are mostly focused on non-computing applications. Since OFETs are fundamental elements employed in an electronic circuit, the performance of the whole electronic device is correlated with its performance. The development of high performance OFET is particularly beneficial for establishing non-silicon-based chip manufacturing in developing countries worldwide. In an attempt to develop a high performance OTFT, double channel bottom gate organic field effect transistor (DCBG OFET) is proposed in this research article. DCBG OFET or OTFT is a single gate device comparable to a bottom gate bottom contact (BGBC) OTFT in structure, but it generates 4 times higher drain current in its conduction channel with identical material composition and structural dimensions compared to its analogous. A comprehensive comparative study has been presented here investigating performance parameters like transconductance, threshold voltage, subthreshold slope, linear and saturation mobility, etc., to determine the functional superiority of the DCBG OFET over other single gate OTFT structures like BGBC, top gate bottom contact (TGBC), and bottom gate top contact (BGTC) OTFTs. It has been observed that DCBG OTFT exhibits a four-fold improvement in the drain current with respect to conventional single gate OTFTs, and staggering 300% enhancements in parameters like transconductance, linear and saturation mobility are also observed in DCBG OFET over other OTFT architectures with matching material configuration and structural dimensions, operational under the identical voltage conditions.
Ilhem Boutana, Mohamed Rachid Mekideche,
Volume 22, Issue 1 (March 2026)
Abstract
Electromagnetic Tube Expansion (EMTE) is a high-velocity forming process that utilizes transient magnetic fields to plastically deform tubular workpieces without physical contact. The process requires the generation of large currents via a capacitor bank, producing intense magnetic pressures to achieve deformation. While EMTE offers significant advantages in precision and efficiency, a comprehensive understanding of the interplay between key working conditions and deformation mechanisms remains crucial for optimizing its performance. This paper presents a numerical investigation into the effects of critical working conditions on the electromagnetic tube expansion process. Using a coupled finite element model, the transient magnetic field and resultant tube deformation are analyzed under varying conditions. The results provide insights into the relationship between process parameters and deformation outcomes, highlighting the potential for optimizing EMTE systems for enhanced efficiency and uniformity. This study contributes to advancing the theoretical and practical understanding of EMTE, by offering guidance for the design of more effective forming strategies and equipment.
Manh-Hung Ha, Duc-Chinh Nguyen, Thai-Kim Dinh, Tran Tien-Tam, Do Tien Thanh , Oscal Tzyh-Chiang Chen,
Volume 22, Issue 1 (March 2026)
Abstract
This paper develops a robust and efficient method for the classification of Vietnamese Sign Language gestures. The study focuses on leveraging deep learning techniques, specifically a Graph Convolutional Network (GCN), to analyze hand skeletal points for gesture recognition. The Vietnamese Sign Language custom dataset (ViSL) of 33 characters and numbers, conducting experiments to validate the model's performance, and comparing it with existing architectures. The proposed approach integrates multiple streams of GCN, based on the lightweight MobileNet architecture. The custom dataset is preprocessed to extract key skeletal points using Mediapipe, forming the input for the multiple GCN. Experiments were conducted to evaluate the proposed model's accuracy, comparing its performance with traditional architectures such as VGG and ViT. The experimental results highlight the proposed model superior performance, achieving an accuracy of 99.94% test on the custom ViSL dataset, reach accuracy of 0.993% and 0.994% on American Sign Language (ASL) and ASL MINST dataset, respectivly. The multi-stream GCN approach significantly outperformed traditional architectures in terms of both accuracy and computational efficiency. This study demonstrates the effectiveness of using multi-stream GCNs based on MobileNet for ViSL recognition, showcasing their potential for real-world applications.
Davood Maleki, Abolfazl Halvaei Niasar,
Volume 22, Issue 1 (March 2026)
Abstract
In electric propulsion systems for high-power applications, multi-phase Permanent Magnet Synchronous Motors (PMSMs) are highly advantageous due to their fast dynamic response and high reliability. This study investigates a twelve-phase PMSM with double stator windings, where each winding is powered by a single-phase H-bridge inverter. The control of both H-bridge inverters for each phase is managed by a dedicated microcontroller. Given the independence of the control systems (microcontrollers) and the absence of data exchange between them, the modeling is conducted in the 12-phase stationary reference frame. To address non-sinusoidal back-EMF phase voltages and mitigate torque ripple, a harmonic current injection method is independently applied to each phase. A model-free predictive current and speed controller (MFPCSC), based on an ultra-local model, is employed, replacing conventional PI or hysteresis current controllers. Additionally, extended state observers (ESOs) are designed to estimate uncertainties and parameter mismatches. Under fault conditions, a fault-tolerant control strategy is implemented, where the current angle of healthy windings is adjusted to suppress the second harmonic in the remaining healthy windings, thereby reducing torque ripple. The effectiveness of the proposed control methods is validated through simulations, both under normal operating conditions and various fault scenarios.
Mohammad Ali Razavi, Farid Tootoonchian, Zahra Nasiri Gheidari,
Volume 22, Issue 1 (March 2026)
Abstract
Synchros are electromagnetic sensors utilized to determine the angular position of a rotating shaft. This paper examines the impact of leakage flux from the Rotary Transformer (RT) on the induced voltages and the position detection accuracy of the Wound-Rotor (WR) synchro. Various methods are proposed to mitigate the negative effects of leakage flux from the RT. The leakage flux paths, which couple with the signal winding, are identified. Based on this analysis, the optimal distance between the sensor and the RT is calculated to minimize the adverse effects of leakage flux on the synchro's accuracy. Additionally, the RT structure is modified to reduce the leakage flux. Another effective approach involves the use of Electromagnetic Interference (EMI) shielding. In this context, a shield frame is designed for the RT, and the impact of different shield materials on reducing leakage flux is investigated. The results show that a copper-based shield significantly reduces the adverse effects of leakage flux and improves the sensor’s accuracy. To evaluate the effectiveness of the proposed methods, they are assessed through 3-D Time-Stepping Finite Element Analysis (3-D TSFEA) and experimental measurements on a prototype sensor. The experimental results show close agreement with the 3-D TSFEA, confirming the accuracy of the findings.
Hamid Ebrahimi, Hossein Torkaman, Alireza Sohrabzadeh, Hamid Javadi,
Volume 22, Issue 1 (March 2026)
Abstract
Mohammad Negintaji, Aghil Ghaheri, Ebrahim Afjei,
Volume 22, Issue 1 (March 2026)
Abstract
In the rapidly advancing domain of wireless power transfer systems, particularly for electric vehicle charging, the design of the magnetic coupler plays a crucial role in determining both system efficiency and practical implementation. Variations in coupler system designs lead to differences in self-inductance, mutual inductance, and AC resistance, directly impacting the energy transfer efficiency and power delivery capability of the system. This paper proposes a novel coil design for wireless power transfer systems, incorporating Double-DZ (DDZ) and Quadrature (Q) coils to improve lateral and yaw misalignment tolerance. The proposed design integrates the advantageous features of three structures—SDDP, DDQP and TTP—to introduce a novel configuration, DDZ-DDQZ, which enhances system stability and performance. By increasing misalignment tolerance, this method substantially enhances the robustness and real-world feasibility of wireless power transfer for electric vehicle charging.
