Journal of Electronics and Electrical Engineering

Fast and Scalable Simulation Framework for Intensive Power Electronics Simulation through Advanced Computing Techniques

Cayden Wagner — 2025-02-28

Power electronics are widely used in power and energy systems, such as electrified transportation and renewable energy systems. These systems are increasing related simulations' size and complexity, resulting in longer computation times. Advanced computing techniques offer new tools for efficient simulation while designing and simulating complex energy systems. This paper introduces high-performance computing for intensive power electronics simulation and demonstrates resultant simulation speedup in a quantified and scalable manner. First, a quantitative study is performed to compare a slower-than-real-time (STRT) simulation benchmark and the proposed faster-than-real-time (FTRT) simulation through a single power electronics building block (PEBB) case study. The impact of switching frequencies in the range of tens to hundreds of kHz considering wide bandgap (WBG) power semiconductors is also investigated. The simulation speed is observed to be accelerated by a factor of 43.8 when using high-performance computing techniques compared to the sequential-based simulation benchmark. Next, a scalable simulation framework is proposed for expanding a single PEBB to an energy system consisting of multiple PEBBs. The framework leverages the high-performance programming language Julia with multi-threaded parallel computing capabilities to reduce the computational burden of power system simulation. The performance gains from the case study demonstrate an average speedup of 2540 times in a 15.0 s multi-PEBB simulation case study compared to its baseline version, with maintained simulation accuracy and ensured scalability.

Comprehensive Survey on Radar Systems and Its Target Classification Techniques

Paramveer Singh — 2025-02-21

This paper surveys target classification techniques in radar systems, focusing on the transformative role of artificial intelligence in enhancing detection and classification capabilities. It reviews the evolution of radar architectures, emphasizing their design, functionality, and key parameters that drive performance. The study spans a range of approaches, from traditional machine learning to advanced deep learning methods, including CNNs, RNNs, self-attention mechanisms, vision transformers, and 2D-SPS. These innovations enable breakthroughs in micromotion detection, background noise reduction, and prediction accuracy. By highlighting applications across various industries, this work provides valuable insights to researchers and engineers, paving the way for advancements in radar technology driven by robust hardware and sophisticated algorithms.

Modeling, Control, and Simulation of a Common-Emitter Switched Amplifier with a Voltage-Variable Gain

José M. Campos-Salazar — 2025-02-20

A novel topology of a switched amplifier configured as a common-emitter voltage variable gain amplifier, along with the implementation of a control system aimed at regulating the output voltage is introduced in this article. A key focus of this work is addressing the challenge of output voltage regulation in the presence of variations in voltage gain caused by changes in the output load. The proposed topology integrates a standard common-emitter amplifier with an additional switch connected to the emitter terminal, which enables implementing an efficient control over the amplifier's voltage gain. The feasibility and operation of the presented system are satisfactorily evaluated through simulation studies.

Design of Compact Open-Ended Wrench-Shaped Patch Antenna for 5G Sub-6 GHz Band Applications

Mahadi Hassan — 2025-02-17

The 5G network requires higher frequency bands as the Sub-6 GHz to handle vast amounts of data and to provide larger bandwidth. This study proposes a novel open-ended wrench-shaped patch antenna with small dimensions of 24 × 32 × 1.6 mm³ to achieve wideband operation in the Sub-6 GHz range. The antenna is etched onto an FR-4 substrate and has dimensions of 1.6 mm in height, a loss tangent of 0.025, and a relative permittivity of 4.3. The intended antenna is excited by a 50 Ω microstrip line, and the simulation is performed using CST software. The impedance matching and antenna bandwidth are improved by introducing a slotted patch plane with a defective ground structure. With two resonance frequencies of 3 GHz and 4.55 GHz, the suggested antenna has a gain of 1.91 dB to 2.90 dB, a directivity of 2.62 dB to 4.13 dB, a return loss of −58.5 dB and −28.4 dB, and a VSWR of 1.002 and 1.08. The wrench's open-ended design provides a broad 3.2 GHz impedance bandwidth and a maximum radiation efficiency of 85.7% in the frequency range of 2.6 to 5.8 GHz, encompassing multiple crucial bands utilized for various applications, including 5G. The design offers significant size reduction while maintaining excellent performance characteristics suitable for 5G wireless devices operating frequency of Sub-6 GHz. The suggested antenna has been built as an experimental prototype, and the results of the measurement and modeling of the return loss parameter coincide quite well.

Modeling and Control of the X-Filter for Enhanced Pulp Mill Performance

José M. Campos-Salazar — 2025-02-17

The dynamic performance of control strategies for an X-filter process is critically analyzed, emphasizing the advantages of model predictive control (MPC) over traditional proportional-integral (PI) control. A detailed simulation model, grounded in the linearized expressions of the X-filter process, was developed using MATLAB-Simulink, with parameters systematically defined and tested under various disturbance scenarios. Key performance indicators, including steady-state behavior, oscillation magnitude, and control effort, were assessed. Results demonstrate that MPC significantly enhances system responsiveness, achieving a steady state more rapidly than PI controllers, with notable reductions in oscillatory behavior across key process variables. Specifically, oscillations in the manipulated variable m_i were effectively mitigated under MPC control, thereby safeguarding hydraulic pump integrity. Statistical analysis of standard deviations for controlled variables revealed that MPC reduces variability in h₁, h₂, and dp by 9%, 24%, and 32% respectively, underscoring its superior ability to maintain stability amidst high-frequency noise and external disturbances. The average position deviation for manipulated variables further illustrates the efficiency of MPC, with reductions of up to 92% in specific instances. Robustness testing confirms MPC's resilience to disturbances in critical input variables, showcasing its adaptability in complex industrial environments. Overall, the findings affirm that MPC not only optimizes set-point tracking but also enhances process control precision, providing a compelling case for its implementation in advanced industrial applications.

A Comprehensive Review of Direction of Arrival (DoA) Estimation Techniques and Algorithms

Saanvi Kulkarni — 2025-02-10

Direction of Arrival (DOA) estimation is a pivotal aspect of Array Signal Processing (ASP) with significant implications for the performance of modern communication systems. This paper provides a comprehensive review of DOA estimation techniques, encompassing both classical and advanced algorithms. Key methods such as MUSIC, ESPRIT, and their variations as well as Beamforming techniques are analysed for their theoretical foundations, computational complexity, and performance under various conditions. MATLAB simulations are conducted to evaluate the impact of critical parameters such as array element spacing, array geometry, number of snapshots, and signal incidence angle differences on estimation accuracy. Special attention is given to the challenges and enhancements in DOA estimation for MIMO systems, highlighting future directions in adaptive and machine learning-based approaches. The study emphasizes the potential of DOA estimation in applications spanning radar, sonar, wireless communication, and beyond, aiming to bridge gaps between current methodologies and emerging requirements.

Design, Dynamic Modelling, Simulation and Control of a Solar Powered Sucker Rod Oil Pump

Charles Aimiuwu Osaretin — 2025-01-23

The sucker rod pump is a crucial artificial lift system widely deployed in the oil industry to extract crude oil from producing wells. Accurate modelling of the sucker rod pump has become essential as a viable strategy for optimizing performance, and ensuring both efficient and economic operation. This paper presents a comprehensive methodology for the design, dynamic modelling, simulation, and control of a solar-powered sucker rod oil pump. It combines load modelling of the sucker rod pump using SolidWorks with design, dynamic modelling, simulation, and control of the solar microgrid in Matlab's Simscape and Simulink. The model seamlessly integrates the mechanical and electrical systems with 100%renewable energy to power the sucker rod pump system. This approach combines the solar photovoltaic system, battery charge control system, battery energy storage system, step-up transformer, and the squirrel cage induction motor, which serves as the electric motor prime mover. The surface pump model is first developed in SolidWorks and then converted to Simscape, the rating of the pump is then implemented as a load in the solar-powered electrical microgrid. Environmental conditions such as solar irradiance and ambient temperature for summer and winter are obtained from data repositories and included in the modelling and analysis of the overall system performance demonstrating stable operation, robustness, and resilience to changing environmental and operational conditions.

Investigation into Shaped Wide-Beam Reflectarray Surfaces Reflectors as Passive Repeaters in Wireless Networks

Peter Callaghan — 2025-01-19

This paper investigates the use of a Reflectarray Surface (RAS) to provide a shaped beam for use as a passive repeater in a wireless network. A shaped beam can be desirable as it may provide coverage over a dead-spot region. Examples of a flat-topped and sloping top shaped beams having a nominal beamwidth of 30^◦ and a steering angle of 40^◦ at 10 GHz are investigated, designed using the particle swarm optimizer in MATLAB. Measurement and simulation from CST show reasonable agreement to the 'array factor' synthesis patterns but display practical detuning effects that may limit this approach. Additionally, it was noted element factor has a more significant impact on such beam shaping.

Improved Transmission Line Relay Algorithm Based on Signum Function of Incremental Currents

Abdul Waheed Kumar — 2025-01-17

Transmission lines are a key part of the power system because they carry power from one end to the other. In case of a fault, the power transfer is perturbed, and the equipments on generation side as well as on the load side can get damaged. Transmission lines carry power from generation end to load end, so it is very important to keep the transmission lines protected. A swift protection system is necessary for the power system. For a quick protection system, rapid fault detection is crucial. A novel method for detecting as well as classifying the faults on transmission lines is reported in this paper. The direction of incremental current along the transmission line's two ends forms the base of this technique and uses a modified signum function. The effectiveness of the said technique is validated by simulating signals in a PSCAD/EMTDC environment on a 50 Hz, 230 kV, 5-bus network. The parameters considered in this study are the line loading, DC offset, fault location and the fault resistance (FR). The FR values considered for simulation purposes range from 0.01 ohm to 1000 ohms. Two types of line structures have been adopted, viz., first, a line connecting generator bus (PV bus) to a load bus (PQ bus) (L_GL) and second, a line connecting two generator buses (L_GG). Detailed results of this study show that the relay detects all internal faults with different loading levels and various FR values. The maximum operating time of the relay is ascertained as 4 ms. The technique has also been validated on IEEE 30-bus system.

Robust Nonlinear Control for Synchronising and Regulating Neural Activity

Sebastián Martínez — 2025-01-09

Modulating neural activity in a systematic manner holds significant potential for advancing the understanding of brain functions and improving therapeutic strategies. To forecast the dynamics behind several brain activities, numerous neurobiological models have been developed, targeting both individual neurons and entire neural populations. In this context, control systems emerge as powerful tools for effectively linking inputs, such as neural stimuli, to measurable outputs. This study introduces a control framework aimed at regulating neural-mass activity, which has promising applications in pattern tracking, including rhythm generation and phase synchronisation. Given the strong connection of these mechanisms to real brain computations, the presented approach offers biologically relevant insights. To demonstrate this, the Wilson-Cowan model is used, in which stimuli are delivered via light signals to genetically engineered neurons expressing light-sensitive actuators. This proof of concept provides a foundation for future experimental applications in neurobiological systems control. Furthermore, building on previous results, this work integrates opsin dynamics, of the channelrhodopsin and halorhodopsin-type, to accurately model the optogenetic activation channels, enhancing the description of the actuation process.

The Threat of Adversarial Attacks against Machine Learning in Network Security: A Survey

Olakunle Ibitoye — 2025-01-08

Machine learning models have made many decision support systems to be faster, more accurate and more efficient. However, applications of machine learning in network security face more disproportionate threat of active adversarial attacks compared to other domains. This is because machine learning applications in network security such as malware detection, intrusion detection, and spam filtering are by themselves adversarial in nature. In what could be considered an arm's race between attackers and defenders, adversaries constantly probe machine learning systems with inputs which are explicitly designed to bypass the system and induce a wrong prediction. In this survey, we first provide a taxonomy of machine learning techniques, tasks, and depth. We then introduce a classification of machine learning in network security applications. Next, we examine various adversarial attacks against machine learning in network security and introduce two classification approaches for adversarial attacks in network security. First, we classify adversarial attacks in network security based on a taxonomy of network security applications. Secondly, we categorize adversarial attacks in network security into a problem space vs. feature space dimensional classification model. We then analyze the various defenses against adversarial attacks on machine learning-based network security applications. We conclude by introducing an adversarial risk grid map and evaluate several existing adversarial attacks against machine learning in network security using the risk grid map. We also identify where each attack classification resides within the adversarial risk grid map.

A High-Power Hybrid-Strip Monopulse Antenna Array for Secondary Surveillance Radars

Ahmed Alieldin — 2025-01-02

This paper proposes a novel design of a high-power monopulse antenna array for secondary surveillance radars utilized in air traffic control systems. A novel technique of hybrid-strip technology is applied to the antenna array (composed of stripline for the feeding network and microstrip for the antenna elements) to minimize the effect of the transition between the feeding network and antenna elements. The antenna array consists of two identical mirrored halves. Each half is 2 rows × 6 columns. The antenna elements are rectangular microstrip patches with shorting vias while the feeding network is composed of a combination of synthesized stripline dividers/combiners. A backfill antenna along with a control network is utilized to achieve the monopulse technique and sidelobe suppression. The control network is a stripline rat race attached to couplers. The antenna array achieves an excellent monopulse performance at the uplink (1030 MHz) and the downlink (1090 MHz) with a return loss better than 15 dB, a realized gain of 22.2 dBi and two independent Sum and Diff channels with a Sum-to-Diff ratio of 30 dB at the antenna boresight. The antenna array can handle a peak power of up to 2.7 MW for long-range traffic detection and control. Such performance makes the proposed antenna array a perfect candidate for secondary surveillance radar.