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Comparative study of feedback linearization control for IM taking into account magnetic saturation effects

e-Prime - Advances in Electrical engineering, Electronics and Energy 2025年 12卷

作者： Es-Semyhy, Mustapha Ba-Razzouk, Abdellfattah El haroussi, Mustapha Hilali, Abdelilah Mathematics Computer and Engineering Sciences Laboratory Systems Analysis and Information Processing Team Faculty of Science and Technology Hassan 1st University Settat Morocco Faculty of Sciences Moulay Ismail University Meknes 11201 Morocco

This study examines how the nonlinear characteristics of the magnetic core, where the magnetic material in an induction machine (IM) exhibits a nonlinear relationship between magnetizing current and resulting flux, affect the performance of control systems. In typical IM operation, these nonlinearities lead to noticeable changes in inductance values, complicating accurate flux estimation. To address this, we develop a nonlinear observer (NLO) that explicitly incorporates the effects of the magnetic core's nonlinearity for rotor flux estimation. The observer gain is designed using a Lyapunov stability framework to ensure exponential convergence of the estimation error under varying flux conditions. This approach is compared with a conventional full-order Luenberger observer (LO) that assumes a simple, linear magnetization characteristic. Within the FOC framework, two feedback linearization strategies are evaluated. The FL sat takes into account the non-linear variations in machine inductances caused by saturation, enabling a more accurate representation of IM dynamics. However, this approach is more complex to calculate because of the nonlinear terms. The FL unsat simplifies control design by neglecting the effects of magnetic saturation, thus reducing computational requirements. Despite its simplified structure, FL unsat delivers comparable performance over the nominal speed and flux operating range. The results highlight a trade-off between dynamic modeling fidelity and control accuracy, offering valuable insights for the design of controllers and observers for IM. While FL sat is well suited to scenarios requiring high accuracy and dynamic tracking, FL unsat emerges as a pragmatic alternative for applications favoring simplicity and real-time implementation. Quantitative measurements further support these results: under constant resistances, the proposed NLO achieves an absolute integral error (IAE) of 0.0133 in rotor magnetization current tracking compared to 1.0

关键词： Feedback linearization control (FLC) Induction machines (IM) Luenberger observer (LO) Magnetic saturation Nonlinear observer (NLO) Resistance variation Rotor flux estimation

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A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions

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IEEE Communications Surveys and Tutorials 2025年

作者： Boateng, Gordon Owusu Sami, Hani Alagha, Ahmed Elmekki, Hanae Hammoud, Ahmad Mizouni, Rabeb Mourad, Azzam Otrok, Hadi Bentahar, Jamal Muhaidat, Sami Talhi, Chamseddine Dziong, Zbigniew Guizani, Mohsen Khalifa University KU6G Research Center Department of Computer Science Abu Dhabi United Arab Emirates Ecole de Technologie Superieure Department of Software and IT Engineering Montreal Canada Lebanese American University Artificial Intelligence and Cyber Systems Research Center Department of CSM Beirut Lebanon Concordia University Concordia Institute for Information Systems Engineering MontrealQC Canada Ecole de Technologie Superieure Department of Electrical Engineering Montreal Canada Department of Computer Science Abu Dhabi United Arab Emirates Khalifa University KU6G Research Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada Mohamed Bin Zayed University of Artificial Intelligence Department of ML Abu Dhabi United Arab Emirates

The rapid evolution of communication networks in recent decades has intensified the need for advanced Network and Service Management (NSM) strategies to address the growing demands for efficiency, scalability, enhanced performance, and reliability of these networks. Large Language Models (LLMs) have received tremendous attention due to their unparalleled capabilities in various Natural Language Processing (NLP) tasks and generating context-aware insights, offering transformative potential for automating diverse communication NSM tasks. Contrasting existing surveys that consider a single network domain, this survey investigates the integration of LLMs across different communication network domains, including mobile networks and related technologies, vehicular networks, cloud-based networks, and fog/edge-based networks. First, the survey provides foundational knowledge of LLMs, explicitly detailing the generic transformer architecture, general-purpose and domain-specific LLMs, LLM model pre-training and fine-tuning, and their relation to communication NSM. Under a novel taxonomy of network monitoring and reporting, AI-powered network planning, network deployment and distribution, and continuous network support, we extensively categorize LLM applications for NSM tasks in each of the different network domains, exploring existing literature and their contributions thus far. Then, we identify existing challenges and open issues, as well as future research directions for LLM-driven communication NSM, emphasizing the need for scalable, adaptable, and resource-efficient solutions that align with the dynamic landscape of communication networks. We envision that this survey serves as a holistic roadmap, providing critical insights for leveraging LLMs to enhance NSM. © 1998-2012 IEEE.

关键词： Resource allocation

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Rectangular Microstrip Patch Antenna Design and Performance Analysis for Wireless Applications 1st

Rectangular Microstrip Patch Antenna Design and Performance ...

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1st International Conference on Electrical systems and Smart Technologies, ICESST 2024

作者： Bendaoued, Mohammed Elmajid, Hassan Es-saleh, Anouar Lakrit, Soufian El Fezazi, Nabil Alvarez, Teresa LMEET Laboratory Faculty of Sciences and Technology Hassan I University Settat Morocco Research Team in Smart Communications Mohammed V University E3S Research Center EMI Rabat Morocco Mathematics and Information Systems Laboratory FP of Nador Mohammed First University Oujda Morocco Mathematics and Information Systems Laboratory EST of Nador Mohammed First University Oujda Morocco IMD-E Higher School of Technology of Dakhla Ibn Zohr University Agadir Morocco LISAC Laboratory Faculty of Sciences Dhar El Mehraz Sidi Mohammed Ben Abdellah University Fez Morocco Industrial Engineering School Dr. Mergelina S/N University of Valladolid Valladolid47005 Spain

ISBN: (纸本)9783031867040

In the paper, a new technique for building a multi-band antenna array with rectangular split-ring resonators (SRRs) is described. The antenna's analysis and design are studied using simulations. On a low-cost FR4 substrate with a total area of 31,84 × 26,06 mm2, the antenna is mounted. The antenna array based on SRR exhibits three-band resonances with good gain characteristics. The simulations focus on calculating resonance frequencies, return loss, and radiation patterns in order to confirm the practicality and applicability of the proposed antenna concept. The Method of Moments (MOM) in Advanced Design System (ADS) software serves as the basis for the electromagnetic solution used in these simulations. Working inside the 3.5 GHz, 4 GHz, and 4.22 GHz bands. a verified S11 value of less than -10 dB suggests that the impedance matching of this antenna is adequate. It offers gains for the appropriate 6.6 dBi, 7.20 dBi, and 6.3 dBi frequency ranges. The antenna is compatible with WLAN (Wireless Local Area Network) 5G (fifth-generation technology standard for cellular networks), LTE (Long Term Evolution), and WiMAX (Worldwide Interoperability for Microwave Access: wireless broadband communication standards based on the IEEE 802.16 well suited for rural areas) wireless network systems, particularly those operating in the sub-6 GHz band. Some of the main features of this antenna are its symmetric radiation patterns, modest size, planar design, and stable gain. These characteristics make it a viable choice for modern S-band microwave wireless communication applications, especially for gadgets that run at frequencies lower than 6 GHz. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Wireless local area networks (WLAN)

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Wheelchair Wheel Design with Transformable “Wheel-Leg” Configuration for Climbing Stairs and Various Surfaces

Wheelchair Wheel Design with Transformable “Wheel-Leg” Con...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Islam Magomedov Timur Aygumov Anzor A. Kanametov Bissnes informatics Kadyrov Chechen state university Grozny Russia Department of software engineering computer technology and automated systems Dagestan State Technical University Dagestan Russia Department of Electronics and Digital Information Technologies Kabardino-Balkarian State University Nalchik Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

The dynamic and uneven terrain of our environment introduces complexity for locomotion vehicles to navigate easily across different settings. Wheelchairs belong to the category of vehicles that require locomotion across various uneven terrains, such as stairs and other partitions. Therefore, the aim of this work is to design a wheel that can travel through various environments without using complex mechanisms. This aim was achieved by creating a novel transformable wheel. This wheel can turn into a legged wheel without using a complex mechanism and, when unnecessary, transform back into a normal wheel. Several simulations were carried out to understand the design's capability to overcome obstacles. In this case, the stair was the obstacle, and the results illustrated that the wheel is capable of climbing stairs without serious issues. Different parameters, such as speed and force, were examined with various values. The results showed that the weight on the wheelchair plays a significant role in climbing. For instance, with lighter weight, the structure moves without major slipping. The roughness of the surface is also related to the wheelchair's ability to reach the top of the stairs. A finer depth of cuts on the surface of the stairs increases the chance of the legged wheel firmly gripping and moving up the stairs.

关键词： Shape Navigation Wheelchairs Wheels Rotors Transforms Stairs Surface roughness Rough surfaces Vehicle dynamics

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Industrial Metaverse in Supply Chain Management: Applications, Concepts, and Open Research Paths 24

Industrial Metaverse in Supply Chain Management: Application...

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Proceedings of the Winter Simulation Conference

作者： Hendrik van der Valk Julia Kunert Niklas Harke Katharina Langenbach Chair for Industrial Information Management TU Dortmund University Dortmund NRW GERMANY and Fraunhofer Institute for Software and Systems Engineering ISST Dortmund NRW GERMANY Chair for Industrial Information Management TU Dortmund University Dortmund NRW GERMANY Dept. of IT in Production and Logistics TU Dortmund University Dortmund NRW GERMANY

ISBN: (纸本)9798331534202

This research study examines the applications of the industrial metaverse in supply chain management. Thus, it reviews and analyzes the up-to-date knowledge along the Supply Chain Operations Reference Model. Therefore, a structured literature review is conducted. We derive six core functionalities of the industrial metaverse in supply chains: visibility and monitoring, prediction, simulation, collaboration, training, and optimization. Furthermore, their presence along the different phases of a supply chain is investigated. Besides the functionalities, the relationship between the industrial metaverse and simulation applications and digital twins is analyzed, and a brief description of possible metaverse architectures is provided. This study additionally derives research gaps within the emerging field of metaverse applications and research and defines paths to tackle them.

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An anonymous and privacy-preserving lightweight authentication protocol for secure communication in UAV-assisted IoAV networks

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Computer Communications 2025年 239卷

作者： Shariq, Mohd Jamil, Norziana Rawat, Gopal Singh Chaudhry, Shehzad Ashraf Masud, Mehedi Cangelosi, Angelo Department of Information Systems and Security College of IT UAE University P.O.Box 15551 Al Ain Abu Dhabi United Arab Emirates Bennett University Greater Noida201310 India Department of Computer Science and Information Technology College of Engineering Abu Dhabi University Abu Dhabi United Arab Emirates Department of Software Engineering Faculty of Engineering and Architecture Nisantasi University Istanbul34398 Turkey Department of Computer Science College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Manchester Centre for Robotics and AI University of Manchester United Kingdom

With the rapid proliferation of the Internet of Things (IoT), autonomous vehicles (AVs), or self-driving cars, rely heavily on real-time data sharing and message exchanges over wireless networks. AVs use sensors, artificial intelligence, machine learning, and advanced algorithms to perform various functions, enabling users to operate without human intervention. Owing to the flexibility and high mobility of drones, they could aid in the operations of AVs. However, the security and privacy are the main concerns;specifically, the threat of physical capture and violation of anonymity are the main hurdles for realization of secure communication among the AVs and drones. To address these challenges, we propose an anonymous and provably Secure Lightweight Authentication Protocol for unmanned-aerial-vehicle-assisted Internet of Autonomous Vehicles (SLAP-IoAV). The proposed protocol uses cryptographic primitives such as exclusive-OR operations, elliptic-curve cryptography, collision-resistant one-way hashing, and concatenation to ensure robust security. An informal security analysis found that SLAP-IoAV is secure against several known attacks, and a performance analysis established that the protocol has less computational and communication overhead than existing competitive protocols. Additionally, Scyther simulation results confirm that no security vulnerabilities are present. Overall, our protocol delivers superior security and performance, making it well-suited to real-world applications in the AV industry. © 2025 Elsevier B.V.

关键词： Authentication Protocol

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Family of Mutually Uncorrelated Codes for DNA Storage Address Design

IEEE Transactions on Nanobioscience

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IEEE Transactions on Nanobioscience 2025年 PP卷 PP页

作者： Liu, Zhenlu Cao, Ben Shao, Qi Zheng, Yanfen Wang, Bin Zhou, Shihua Zheng, Pan Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China University of Canterbury Upper Riccarton Department of Accounting and Information Systems Christchurch8140 New Zealand

Deoxyribonucleic acid (DNA) has become an ideal medium for long-term storage and retrieval due to its extremely high storage density and long-term stability. But access efficiency is an existing bottleneck in DNA storage, especially the lack of high-quality random access address sequences. Therefore, in this paper, we report a series of approaches based on k-weakly mutually uncorrelated (k-WMU) codes to design the address sequence to improve the access efficiency of DNA storage. To address the problem of DNA sequences that are poorly scalable at the base level, we propose a 0-m-ruling coding scheme combined with k-WMU codes that can make address sequences avoid generating secondary structure with stem lengths ranging from 3 to 9. Based on the decoupled structure, We further extend the k-WMU codes with error correction function while satisfying combinatorial biological constraints. In order to investigate the performance of the designed address sequences for real-world applications, we perform simulation experiments based on thermodynamic properties and error correction capability as well as compared the minimum free energy (MFE), melting temperature (TM), and average decoding success rate (ADSR) with previous work. The results show that designed address sequences have a high MFE value and ADSR and a substantial reduction in TM-variance while satisfying the combinatorial biological constraints. As the quality of address sequences improves, this will help to achieve accurate random access as well as enhance the robustness of the DNA storage system. © 2002-2011 IEEE.

关键词： DNA sequences

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Loss Functions in Deep Learning: A Comprehensive Review

arXiv

引用

arXiv 2025年

作者： Elharrouss, Omar Mahmood, Yasir Bechqito, Yassine Serhani, Mohamed Adel Badidi, Elarbi Riffi, Jamal Tairi, Hamid Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates Department of Information Systems College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Informatics Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fez Morocco

Loss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the difference between predicted outputs and ground truth labels, guiding the optimization process to minimize errors. Selecting the right loss function is critical, as it directly impacts model convergence, generalization, and overall performance across various applications, from computer vision to time series forecasting. This paper presents a comprehensive review of loss functions, covering fundamental metrics like Mean Squared Error and Cross-Entropy to advanced functions such as Adversarial and Diffusion losses. We explore their mathematical foundations, impact on model training, and strategic selection for various applications, including computer vision (Discriminative and generative), tabular data prediction, and time series forecasting. For each of these categories, we discuss the most used loss functions in the recent advancements of deep learning techniques. Also, this review explore the historical evolution, computational efficiency, and ongoing challenges in loss function design, underlining the need for more adaptive and robust solutions. Emphasis is placed on complex scenarios involving multi-modal data, class imbalances, and real-world constraints. Finally, we identify key future directions, advocating for loss functions that enhance interpretability, scalability, and generalization, leading to more effective and resilient deep learning models. © 2025, CC BY.

关键词： Deep learning

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Gender Classification from Pashto Handwritten Text Images

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IEEE Access 2025年 13卷 81736-81754页

作者： Sultan, Khan Ahmad, Riaz Muhammad, Siraj Almutairi, Sulaiman Abohashrh, Mohammed Ullah, Khalil Namoun, Abdallah Hussain, Ibrar Shaheed Benazir Bhutto University Department of Computer Science Dir Upper Khyber Pakhtunkhwa Sheringal75660 Pakistan Qassim University College of Applied Medical Sciences Department of Health Informatics Qassim52571 Saudi Arabia King Khalid University College of Applied Medical Sciences Department of Basic Medical Sciences Abha61421 Saudi Arabia University of Malakand Department of Software Engineering Dir Lower Khyber Pakhtunkhwa Malakand18800 Pakistan Islamic University of Madinah AI Center Faculty of Computer and Information Systems Madinah42351 Saudi Arabia Shaheed Benazir Bhutto University Sheringal Quality Enhancement Cell Khyber Pakhtunkhwa Dir Upper75660 Pakistan

Computer vision (CV) is a subfield of computer science that enables machines to perceive, interpret, and understand visual data. It combines image processing, analysis, and machine learning to extract meaningful insights from images and videos. One key application of CV is the classification of gender from handwritten text images-a complex task, especially in languages such as Pashto due to the intricacy of the script and the limited resources. This research presents a novel approach to gender classification using Pashto Handwritten Text Images (PHTI). The study evaluates and compares the performance of traditional machine learning and modern deep learning models: Support Vector Machine (SVM) and You Only Look Once version 8 (YOLO8), a CNN-based object detection framework. The PHTI dataset, introduced in this study, consists of 36,086 text line images written by 200 male and 200 female native Pashto writers. The goal is to assess how effectively SVM and YOLO8 can classify gender based on visual handwriting patterns in the Pashto language. The experimental results reveal that YOLO8 outperforms SVM in classification accuracy. Although SVM, a widely used machine learning model, achieved an accuracy of 61.29%, YOLO8 reached a significantly higher accuracy of 77% in the same data set. This performance gap highlights the advantages of using advanced deep learning models for complex pattern recognition tasks in CV. This research provides a pioneering contribution by focusing on Pashto, a low-resource language, in the context of gender classification using handwritten text images. It opens new pathways for applying CV in regional languages and supports the development of intelligent systems capable of handling various scripts. © 2013 IEEE.

关键词： Machine vision

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Towards Gradient Equalization and Feature Diversification for Long-Tailed Multi-Label Image Recognition

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IEEE Transactions on Multimedia 2025年

作者： Chen, Zhao-Min Cui, Quan Zhang, Xiaoqin Deng, Ruoxi Xia, Chaoqun Lu, Shijian Nanjing University National Key Laboratory for Novel Software Technology Nanjing210093 China Waseda University Graduate School of Information Production and Systems Fukuoka169-8050 Japan Wenzhou University College of Computer Science and Artificial Intelligence Wenzhou325060 China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore

Multi-label image recognition with convolutional neural networks has achieved remarkable progress in the past few years. However, most existing multi-label image recognition methods suffer from the long-tailed data distribution problem, i.e., head categories occupy most training samples, while tailed classes have few samples. This work firstly studies the influence of long-tailed data distribution on existing multi-label image recognition methods. Based on this, two crucial issues of the existing methods are identified: 1) severe gradient imbalance between head and tailed categories, even though re-balancing strategies are adopted;2) the lack of diversity of tail category training samples. To tackle the first issue, this paper proposes a group sampling strategy to create group- wise balanced data distribution. Meanwhile, a dynamic gradient balancing loss is proposed to equalize the gradient for all categories. To tackle the second issue, this paper proposes a diversity enhancement module to fuse the information across all categories, preventing the network from overfitting tail classes. Furthermore, it also balances the gradient, promoting the discriminability of learned classifiers. Our method significantly outperforms the baseline method and achieves competitive performance with state-of-the-art methods on VOC-LT and COCO-LT datasets. Extensive ablation studies are conducted to verify the effectiveness of the essential proposals. © 1999-2012 IEEE.

关键词： Labeled data

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