IEEE Canadian Journal of Electrical and Computer Engineering最新文献

{"title":"A Novel Stabilizer-Based Interface Algorithm for Power Hardware-in-the-Loop Simulation","authors":"Fajar Kurnia Al Farisi;Jian-Hong Liu;Na-De Yang;Kuo-Lung Lian;Zhi-Kai Fan","doi":"10.1109/ICJECE.2026.3696455","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3696455","url":null,"abstract":"Power hardware-in-the-loop (PHIL) is a type of real-time simulation (RTS) in which power hardware under test (PHUT) interacts with a simulated power system through an interface algorithm (IA). A variety of IAs for PHIL have been proposed and investigated in the literature. Due to its straightforward implementation, the ideal transformer model (ITM) is the most widely used IA in PHIL simulations. Building upon the ITM framework, several IAs, including two representative extended models—the partial circuit duplication (PCD) and the damping impedance method (DIM)—have been developed and implemented. These extended models require maintaining a predefined impedance ratio between the PHUT and the remainder of the simulated system, making their application labor-intensive and technically challenging. Moreover, these models inherently suffer from critical stability issues, leading to unstable interactions between the simulated system and the PHUT. To enhance PHIL stability, some advanced IAs adopt a Smith predictor (SP); however, such approaches rely heavily on the fidelity of the system model, thereby limiting their effectiveness in stabilizing PHIL simulations. To fully address stability in PHIL simulations, this article proposes a novel stabilizer-based IA to enhance PHIL simulation stability. The proposed stabilizer-based IA demonstrates a significant enhancement in PHIL simulation stability, particularly under the integration of passive devices or active components such as inverter-based resources (IBRs), compared to existing IAs. In addition, under harmonic injection conditions in PHIL simulations, the proposed method provides enhanced simulation fidelity by improving the reproduction of distorted interface voltage and current waveforms between the simulated system and the PHUT. PHIL simulations conducted on the PHIL system are presented to validate the effectiveness of the proposed approach.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"510-524"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148627847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring YOLO Architectures for Radar-Based Flying Object Classification Using Micro-Doppler Signatures","authors":"Megha Kataria;Brejesh Lall","doi":"10.1109/ICJECE.2026.3686010","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3686010","url":null,"abstract":"The increasing use of unmanned aerial vehicles (UAVs) across civilian and defense applications has created a need for reliable, real-time drone classification methods. Radar-based micro-Doppler signatures provide distinctive motion patterns that enable effective target identification under various environmental conditions. While deep learning has been applied to radar spectrograms, most studies use conventional classifiers that lose spatial detail critical for interpreting micro-Doppler features. This article presents the first systematic benchmarking of the You Only Look Once (YOLO) family (YOLOv1–YOLOv8) for radar-based UAV classification. Each model was adapted from its detection architecture by redesigning the detection head for classification and trained using the DIAT–μSAT dataset containing six aerial target classes. Models were evaluated across multiple metrics, including accuracy, precision, recall, F1-score, model size, and inference speed. Grad-CAM visualization was used to analyze spatial attention across YOLO versions. Results show that YOLOv8 achieves the best balance between accuracy (93.1%) and efficiency, outperforming both earlier YOLO models and standard CNN-based classifiers. The study establishes a unified benchmark for YOLO architectures on radar data and demonstrates their potential for efficient real-time radar classification.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"285-298"},"PeriodicalIF":1.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148141552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Secure Hybrid Deep Learning Model for Honeypot Security and Monitoring System Using Quantum Dilated Convolutional–Fuzzy–Maxout Network","authors":"Rajasekar Kaniappan;V. Jamuna","doi":"10.1109/ICJECE.2026.3689042","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3689042","url":null,"abstract":"Due to the rise of computing techniques and their prevalent applications, cloud computing (CC) has been considered as a significant approach for secure data storage. Network firewalls protect the servers from harmful traffic and unauthorized access. Still, security solutions like intrusion detection and prevention systems (IDPSs) and antivirus (AVs) are complex and consume more time. For solving such issues, a honeypot is considered a popular technique for attaining network security. The discovery of honeypots, which are deliberately created as decoy systems to draw attention to and identify malicious behavior or illegal access, is an essential component of cybersecurity. Honeypots work as bait to help detect security flaws, learn attack patterns, and mitigate possible risks before they have a substantial impact on actual systems. This is essential because honeypots can identify undiscovered dangers, aid in the prevention of future assaults, and enhance network security by giving real-time information on possible intrusions. In CC, identifying honeypots is essential because they provide another line of protection by spotting complex threats that might elude traditional security procedures. Cloud administrators may strengthen intrusion detection, improve data security, and increase the overall resilience of the system by locating and evaluating honeypots. In this research, a novel quantum dilated convolutional–fuzzy–maxout network (QDCFMNet) is developed for honeypot identification in cloud environments. The prime process is the simulation of cloud nodes. The input log files are subjected to data preprocessing using a linear normalization approach. The features from the normalized log files are fused using the deep Kronecker network (DKN) with Kulczynski similarity. The synthetic minority oversampling technique (SMOTE) augments the dimension of the log file. The proposed QDCFMNet is employed for honeypot identification. In addition, SHapley Additive exPlanations (SHAP) is incorporated to analyze the contribution of input features and to improve the interpretability of the proposed model. Furthermore, the metrics like precision, recall, and 1-score are used to compute the efficiency of the QDCFMNet-based honeypot identification, which attains the finest values of 90.59%, 91.72%, and 91.15%, respectively.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"312-320"},"PeriodicalIF":1.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148141581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and Development of 11-Level Boost Multilevel Inverter With New Switching Scheme","authors":"Karunakaran Eddu;Suresh Yellasiri;Bhukya Nageswar Rao;Anup Kumar Panda","doi":"10.1109/ICJECE.2026.3693574","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3693574","url":null,"abstract":"This article proposes a novel 11-level boost multilevel inverter (BMLI) in combination with a novel fuzzy switching scheme. The proposed inverter is composed of a reduced number of components, with 12 switches, 2 diodes, 3 capacitors, and a single-DC source, operating with a self-voltage balancing mechanism without additional sensors. The proposed fuzzy switching scheme integrates both high frequency and fundamental frequency with rule-based membership functions (MFs) by completely eliminating the complex logic gate design, high-memory lookup tables, and enhancing the output waveform quality. Furthermore, MFs are derived from the optimized firing angles, which are generated by utilizing an enhanced selective harmonic elimination pulsewidth modulation (SHEPWM) and sine quantizer methods. The proposed BMLI offers a distinct advantage, in which selected switches operate at high frequency, while the remaining switches operate at the fundamental frequency, thereby enhancing waveform quality, reducing harmonic distortion, and minimizing switching losses. Power loss and thermal stress analyses are conducted to demonstrate the performance capability of the proposed inverter. A quantitative comparison of the proposed inverter with former multilevel inverters has been carried out to address its potential. The effectiveness and performance of the proposed BMLI are validated through experimental verification on a scale-down hardware prototype.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"406-417"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Induced L∞-Norm Bounded Stability of Linear Systems With Time-Varying Delay and Application to DC Motor Control","authors":"Hilal Bingöl;Gökhan Soysal;Klaus Werner Schmidt","doi":"10.1109/ICJECE.2026.3707925","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3707925","url":null,"abstract":"This article develops a controller-synthesis method for induced <inline-formula> <tex-math>${mathcal {L}}_{infty } $ </tex-math></inline-formula>-norm bounded stability of time-delay systems under disturbances. First, a general sufficient bounded-stability condition is derived using a Lyapunov–Krasovskii functional. Next, this condition is specialized to linear systems with time-varying input delay and expressed as linear matrix inequalities (LMIs) for state-feedback controller synthesis. The applicability of the proposed framework is illustrated through a DC motor control example with various input/output configurations. In addition, comparative results are provided for constant-delay, time-varying-delay, and delay-free controller designs, including a comparison with an <inline-formula> <tex-math>${mathcal {H}}_{infty } $ </tex-math></inline-formula>-based controller.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"536-544"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148749111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IEEE Canadian Journal of Electrical and Computer Engineering","authors":"","doi":"10.1109/ICJECE.2026.3698725","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3698725","url":null,"abstract":"","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"C2-C2"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11692342","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Small-Signal Stability of Hybrid Grid-Forming and Grid-Following Converter Systems: Grid Strength Effect","authors":"Xing Yao;Meng Zhan;Yutao Pan","doi":"10.1109/ICJECE.2026.3697739","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3697739","url":null,"abstract":"As the penetration of renewable energy continues rising and the grid conditions become increasingly complicated, the instability phenomena have happened more frequently, but their mechanisms remain uncovered. This article investigates the small-signal stability of a 100% hybrid grid-forming (GFM) and grid-following (GFL) converter system and uncovers the general role of grid strength. A general state-space model is developed, which is easily applicable to any multiconverter system. Based on the state-space matrix, root locus, and participation factor analyses, the stable and unstable parameter domains characterized by different instability modes are obtained, which reveal that they occur as either a pure single-converter instability behavior or a superposition of different instability types. A detailed parametric analysis is conducted to clarify these distinct instability modes. In addition, it is found that the stiff-grid-instability of the GFM is a local effect, determined largely by the grid strength along the interconnection path between any two GFM converters. In contrast, the weak-grid-instability of either GFM or GFL converter is a global effect, which is triggered when the overall grid strength is weakened. All these findings are broadly supported by theoretical analysis and time-domain simulations and they can provide improved insights in the grid-strength effects on the stability of large-scale power system dominated by converters.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"472-484"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148509754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Particle Swarm Optimization-Aided Enhanced Belief Propagation Bit-Flipping Decoding of Polar Codes","authors":"Guiping Li;Wenhua Zhao;Jiaqi Liu","doi":"10.1109/ICJECE.2026.3713262","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3713262","url":null,"abstract":"Belief propagation bit-flipping (BPBF) decoding for polar codes has attracted growing attention owing to its inherent parallelism and improved frame error rate (FER) compared with the original BP decoding. However, existing improved BPBF algorithms still suffer from either a significant performance gap relative to CRC-aided successive cancellation list (CA-SCL) decoding or excessively high computational complexity. Since the constructed bit-flipping set directly determines decoding performance, we propose an enhanced BPBF decoding scheme that employs particle swarm optimization (PSO) to efficiently identify error-prone bits. Specifically, the PSO adopts multiple particles initialized by channel error probabilities to iteratively explore high-risk bits in continuous space. A dynamic inertia weight is introduced to balance global exploration and local exploitation. Breaking the constraints of conventional single-point greedy search, this scheme leverages the globally optimized particle to deduce a reliable bit-flipping combination within the solution space. The simulation results verify that the proposed decoder achieves prominent FER performance gains while maintaining a lower average computational complexity than existing state-of-the-art BPBF decoders based on weighted metric screening.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"581-591"},"PeriodicalIF":1.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148781122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hardware-in-the-Loop Testbed for Advanced Distribution Management Systems","authors":"Konrad Schmitt;Rajendra Shrestha;Larissa Souto;Pedro Eisenkraemer;Manohar Chamana;Meisam Mahdavi;Stephen Bayne;Luciane Canha","doi":"10.1109/ICJECE.2026.3687411","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3687411","url":null,"abstract":"Advanced distribution management systems (ADMSs) embrace several online and offline monitoring and control features to ensure power delivery with reliability, continuity, and quality. By having data about the system’s topology, ADMS can obtain real-time field measurements to perform further analysis on the network and automatically respond to events or support operators’ decisions. Academia has been advancing the current state of the art of ADMS by proposing more sophisticated solutions that aim to address the ongoing changes in active distribution networks. However, such solutions are commonly tested in offline environments, neglecting the dynamics and challenges related to real-world field equipment and communication protocols. The most faithful power systems solution can get tested before actual deployment is through hardware-in-the-loop (HIL) testing, where electrical systems are simulated in real-time digital simulators, and physical equipment is integrated into the simulator through analog hardwiring and communication protocols. Considering the need for more realistic testing and validation of proposed solutions to facilitate real-world deployment, this research proposes and presents an HIL testbed for ADMS’s testing purposes that may guide future studies in the area. Along with the testbed, an automatic outage restoration ADMS feature is formulated and tested on the proposed HIL system, where the benefits of pushing validation to the most faithful testbed are highlighted.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"299-311"},"PeriodicalIF":1.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148141568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distribution Network Modeling, Parameters, and Metering Data: Test Systems","authors":"Konrad Schmitt;Larissa Souto;Meisam Mahdavi;Manohar Chamana;Stephen Bayne;Luciane Canha;Francisco Jurado","doi":"10.1109/ICJECE.2026.3693137","DOIUrl":"https://doi.org/10.1109/ICJECE.2026.3693137","url":null,"abstract":"After initial development and testing with synthetic data, distribution systems solutions are required to be verified under diverse network topologies and consumption patterns to confirm their deployment feasibility. Even though the literature has presented data for several test distribution networks over the years and smart metering datasets have been made available, finding them according to the research requirements is time-consuming. Especially in reconfiguration and restoration studies, test networks must have a networked topology, which makes the search for models even more limited. Still, the available network models and datasets tend to be oversimplified or omit crucial data and users are often left with the need to make assumptions. This article compiles and presents eight different reconfigurable distribution networks ranging from 12 to 328 nodes and nine smart metering datasets for residential. Along with the compiled data, this article discusses the available and missing information of each model and dataset, while potential assumptions and their impacts are discussed. With that, the main intention of this article is to provide a complete and centralized resource to support the development of various active distribution networks’ studies.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"49 3","pages":"392-405"},"PeriodicalIF":1.9,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}