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Model Reference Adaptive Predictive Current Control of Six-Phase Induction Machine

IEEE Transactions on Industrial Electronics 2025年

作者： Arahal, Manuel R Satue, Manuel G Barrero, Federico Martinez-Heredia, Juana University of Seville Systems Engineering and Automation Department Seville41092 Spain University of Seville Electronics Department Seville41092 Spain

Predictive stator current control (PSCC) is a flexible technique that has been the subject of research in connection with multiphase drives. The flexibility that the cost function (CF) brings finds an obstacle in CF tuning. Intensive trial and error tests are usual in this context. In this article, an adaptive procedure is proposed based on the concept of model reference adaptive control. Unlike previous methods, the proposal provides on-line tuning of PSCC with very little burden. The proposal is motivated by the idea of using optimal weighting factors (WFs) for each operating point. A case study is developed for a six-phase induction machine. The adaptive method includes cross terms and momentum to cope with irregularities in the derivatives with respect to the WF. It is shown that adaptiveness allows crossing the Pareto front of performance indicators. This provides flexibility without optimality loss. The proposal is assessed with real experimentation on a laboratory set-up. © 2025 IEEE.

关键词： Model reference adaptive control

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GACL-Net:Hybrid Deep Learning Framework for Accurate Motor Imagery Classification in Stroke Rehabilitation

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Computers, Materials & Continua 2025年第4期83卷 517-536页

作者： Chayut Bunterngchit Laith H.Baniata Mohammad H.Baniata Ashraf ALDabbas Mohannad A.Khair Thanaphon Chearanai Sangwoo Kang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Computing Gachon UniversitySeongnam13120Republic of Korea Computer Science Department Faculty of Information TechnologyThe World Islamic Sciences and Education UniversityAmman11947Jordan Intelligent Systems Department Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan IT Infrastructure Department Qatrana Cement CompanyAmman11821Jordan Division of Industrial and Logistics Engineering Technology Faculty of Engineering and TechnologyKing Mongkut’s University of Technology North BangkokRayong CampusRayong21120Thailand

Stroke is a leading cause of death and disability worldwide,significantly impairing motor and cognitive *** rehabilitation is often hindered by the heterogeneity of stroke lesions,variability in recovery patterns,and the complexity of electroencephalography(EEG)signals,which are often contaminated by *** classification of motor imagery(MI)tasks,involving the mental simulation of movements,is crucial for assessing rehabilitation strategies but is challenged by overlapping neural signatures and patient-specific *** address these challenges,this study introduces a graph-attentive convolutional long short-term memory(LSTM)network(GACL-Net),a novel hybrid deep learning model designed to improve MI classification accuracy and ***-Net incorporates multi-scale convolutional blocks for spatial feature extraction,attention fusion layers for adaptive feature prioritization,graph convolutional layers to model inter-channel dependencies,and bidi-rectional LSTM layers with attention to capture temporal *** on an open-source EEG dataset of 50 acute stroke patients performing left and right MI tasks,GACL-Net achieved 99.52%classification accuracy and 97.43%generalization accuracy under leave-one-subject-out cross-validation,outperforming existing state-of-the-art ***,its real-time processing capability,with prediction times of 33–56 ms on a T4 GPU,underscores its clinical potential for real-time neurofeedback and adaptive *** findings highlight the model’s potential for clinical applications in assessing rehabilitation effectiveness and optimizing therapy plans through precise MI classification.

关键词： Motor imagery EEG stroke rehabilitation deep learning brain-computer interface

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Conditional Disturbance Compensation-Based Fault-Tolerant Group Consensus Control for MASs: An Event-Based Switching Method

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IEEE Transactions on automation Science and engineering 2025年 22卷 13828-13841页

作者： Liu, Pei-Ming Guo, Xiang-Gui Wang, Jian-Liang Che, Wei-Wei Wu, Zheng-Guang University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering Beijing100083 China University of Science and Technology Beijing Shunde Innovation School Foshan528000 China Beihang University Hangzhou Innovation Institute Autonomous Intelligent Systems Department Hangzhou310051 China Northeastern University College of Information Science and Engineering Shenyang266071 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou310027 China

With respect to the group consensus control for multi-agent systems (MASs) with disturbances and actuator nonidentical and unknown direction faults (NUDFs), this paper proposes a novel fault-tolerant control scheme by incorporating an event-based switching function and a saturation function. The event-based switching function is implemented to directly switch to the desired working mode, thereby reducing invalid switching after a reverse fault. Concurrently, the saturation function, acting at the software level, can not only prevent the instantaneous impact of excessive reverse input caused by a reverse fault, but also eliminate input peaking and state chattering after switching the working mode. It is worth mentioning that the proposed switching-based fault-tolerant control method can avoid the control chocks and excessive control gains as in the existing methods by using Nussbaum functions and thus improve the transient performance. Additionally, for disturbances, the designed conditional disturbance compensation mechanism ensures a smaller steady-state error, and less energy consumption by utilizing beneficial disturbances and compensating for harmful ones. Besides, the conditional compensation mechanism also reduces the saturation error. Finally, the effectiveness of the proposed control scheme are verified through a simulation example of uncrewed aerial vehicles (UAVs). © 2004-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Impact of Carrier Geometries on the Performance of Coaxial Magnetic Gears 24

Impact of Carrier Geometries on the Performance of Coaxial M...

引用

24th International Symposium INFOTEH-JAHORINA, INFOTEH 2025

作者： Dindar, Taner Aktaş, Serkan Ayaz, Murat Yilmaz, Kadir Sezen, Serkan Ankara University Department of Electronic and Automation Ankara Turkey Kocaeli University Department of Machinery and Metal Technologies Kocaeli Turkey Kocaeli University Department of Electric and Energy Kocaeli Turkey Kocaeli University Department of Energy Systems Engineering Kocaeli Turkey

ISBN: (纸本)9798331515799

Magnetic gears offer an effective alternative to traditional mechanical gears by providing advantages such as contactless operation, minimal maintenance requirements, and quieter performance. The carrier, a fundamental component modulating the magnetic coupling between the inner and outer rotors, directly impacts the performance parameters of magnetic gears. This study investigates the effects of different carrier geometries on critical performance metrics such as torque density, torque ripples, and efficiency in coaxial magnetic gear systems. Magnetic gears featuring three distinct carrier structures - polygonal, elliptical, and circular - were modeled and analyzed using the Ansys Maxwell software. The output parameters for all three models were detailed and compared comprehensively. Finite element analysis results demonstrate that polygonal carrier geometry enhances torque density, while an elliptical design effectively reduces torque ripple. © 2025 IEEE.

关键词： Input output programs

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Acceleration-level coordinated control of a dual-arm free-floating space robot under hard joint constraints

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Advances in Space Research 2025年第11期75卷 8122-8139页

作者： Xue, Zhihui Liu, Jinguo Zhang, Xin Zhou, Hao Li, Yangmin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Kowloon999077 Hong Kong School of Electrical and Mechanical Engineering University of Portsmouth PortsmouthPO1 3DJ United Kingdom

Dual-arm space robots are becoming increasingly crucial in on-orbit servicing missions. The online motion control of a dual-arm redundant space robot with hard joint constraints presents significant challenges due to its free-floating base. In this article, we proposed an acceleration-level coordinated control framework to solve hard joint constraints and dynamic singularity. The proposed framework combines a task scheduling strategy to achieve saturation in the null space, so that different tasks can achieve trajectory tracking with minimal task scaling under given joint hard constraints. The framework can achieve efficient online control by sequentially abandoning the use of joints that exceed the joint constraint and reintroducing these commands at their saturation level by projecting them into the appropriate null space. Finally, we verify the tracking performance of the algorithm through numerical simulation and experimental research. By comparing the proposed algorithm with the quadratic programming and pseudo-inverse methods, the algorithm has shown excellent online motion control performance, with a computation time of approximately 1 ms within a single sampling period. © 2025 COSPAR

关键词： Quadratic programming

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Adapting Vision Transformers for Cross-Product Defect Detection in Manufacturing 6

Adapting Vision Transformers for Cross-Product Defect Detect...

引用

6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Nikolakis, Nikolaos Catti, Paolo Fabbro, Luca Alexopoulos, Kosmas Laboratory for Manufacturing Systems and Automation Department of Mechanical Engineering and Aeronautics University of Patras Rio Campus Greece APTIV Connection System Service Italia S.p.A. Strada Del Francese 137 Turin Italy

Advanced defect detection solutions that can easily adapt to different products and defect types are of high value for modern manufacturing companies. A significant challenge in developing and deploying such AI models is ensuring they generalize efficiently across diverse visual domains. This challenge is driven by limited data availability of high quality and the substantial effort required for labeling such datasets. This paper explores the adaptation of a Vision Transformer (ViT), originally trained to identify aesthetic defects in battery modules, for application in moulded plastic parts. By using transfer learning and generative AI techniques, this study evaluates fine-tuning and synthetic data augmentation strategies. The proposed approaches are assessed for their potential to enhance model adaptability and reduce dependency on extensive labelled datasets. A case study involving a battery manufacturing company with real-world data serves as the basis for this evaluation. Our preliminary findings suggest promising directions for enhancing the flexibility and efficacy of AI-driven defect detection systems in diverse manufacturing environments. © 2024 The Authors. Published by Elsevier B.V.

关键词： Distribution transformers

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Physics-informed Echo State Networks for modeling controllable dynamical systems

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Neurocomputing 2025年 639卷

作者： Mochiutti, Eric Antonelo, Eric Aislan Camponogara, Eduardo Department of Automation and Systems Engineering Federal University of Santa Catarina Santa Catarina Florianópolis88040-900 Brazil

Echo State Networks (ESNs) are recurrent neural networks usually employed for modeling nonlinear dynamic systems with relatively ease of training. By incorporating physical laws into the training of ESNs, Physics-Informed ESNs (PI-ESNs) were proposed initially to model chaotic dynamic systems without external inputs. They require less data for training since Ordinary Differential Equations (ODEs) of the considered system help to regularize the ESN. In this work, the PI-ESN is extended with external inputs to model controllable nonlinear dynamic systems. Additionally, an existing self-adaptive balancing loss method is employed to balance the contributions of the residual regression term and the physics-informed loss term in the total loss function. The experiments with two nonlinear systems modeled by ODEs, the Van der Pol oscillator and the four-tank system, and with one differential–algebraic (DAE) system, an electric submersible pump, revealed that the proposed PI-ESN outperforms the conventional ESN, especially in scenarios with limited data availability, showing that PI-ESNs can regularize an ESN model with external inputs previously trained on just a few datapoints, reducing its overfitting and improving its generalization error (up to 92% relative reduction in the test error). Further experiments demonstrated that the proposed PI-ESN is robust to parametric uncertainties in the ODE equations and that model predictive control using PI-ESN outperforms the one using plain ESN, particularly when training data is scarce. © 2025 Elsevier B.V.

关键词： Predictive control systems

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Harmonic Model Predictive Control for Tracking Sinusoidal References and its Application to Trajectory Tracking

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IEEE Transactions on Automatic Control 2025年

作者： Krupa, Pablo Limon, Daniel Bemporad, Alberto Alamo, Teodoro IMT School for Advanced Studies Lucca Italy Universidad de Sevilla Department of Systems Engineering and Automation Seville Spain

Harmonic model predictive control (HMPC) is a recent model predictive control (MPC) formulation for tracking piece-wise constant references that includes a parameterized artificial harmonic reference as a decision variable, resulting in an increased performance and domain of attraction with respect to other MPC formulations. This article presents an extension of the HMPC formulation to track periodic harmonic/sinusoidal references and discusses its use for tracking arbitrary trajectories. The proposed formulation inherits the benefits of its predecessor, namely its good performance and large domain of attraction when using small prediction horizons, and that the complexity of its optimization problem does not depend on the period of the reference. We show closed-loop results discussing its performance and comparing it to other MPC formulations. © 1963-2012 IEEE.

关键词： Predictive control systems

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Bibliometric and Content Analysis of Large Language Models Research in Software engineering: The Potential and Limitation in Software engineering

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International Journal of Advanced Computer Science and Applications 2025年第4期16卷 344-356页

作者： Damayanti, Annisa Dwi Gani, Hamdan Zhipeng, Feng Gani, Helmy Zuhriyah, Sitti Nurani Djabir, St. Nurhayati Wardani, Nur Ilmiyanti Department of Environmental Engineering Faculty of Engineering Hasanuddin University Makassar Indonesia Department of Machinery Automation System ATI Makassar Polytechnic Makassar Indonesia School of Culture Creativity and Media Hangzhou Normal University Zhejiang Hangzhou China Department of Industrial Hygiene Faculty of Public Health Occupational Health and Safety Makassar College of Health Sciences Indonesia Department of Computer System Universitas Handayani Makassar Makassar Indonesia Department of Information Systems and Technology Institut Teknologi dan Bisnis Nobel Indonesia Jl. Sultan Alauddin No.212 Makassar90221 Indonesia Department of Informatics Engineering Universitas Handayani Makassar Makassar Indonesia

Large Language Models (LLM) is a type of artificial neural network that excels at language-related tasks. The advantages and disadvantages of using LLM in software engineering are still being debated, but it is a tool that can be utilized in software engineering. This study aimed to analyze LLM studies in software engineering using bibliometric and content analysis. The study data were retrieved from Web of Science and Scopus. The data were analyzed using two popular bibliometric approaches: bibliometric and content analysis. VOS Viewer and Bibliometrix software were used to conduct the bibliometric analysis. The bibliometric analysis was performed using science mapping and performance analysis approaches. Various bibliometric data, including the most frequently referenced publications, journals, and nations, were evaluated and presented. Then, the synthetic knowledge method was utilized for content analysis. This study examined 235 papers, with 836 authors contributing. The publications were published in 123 different journals. The average number of citations per publication is 1.44. Most publications were published in Proceedings International Conference on Software engineering and ACM International Conference Proceeding Series, with China and the United States emerging as the leading countries. It was discovered that international collaboration on the issue was inadequate. The most often used keywords in the publications were "software design," "code (symbols)," and "code generation." Following the content analysis, three themes emerged: 1) Integration of LLM into software engineering education, 2) application of LLM in software engineering, and 3) potential and limitation of LLM in software engineering. The results of this study are expected to provide researchers and academics with insights into the current state of LLM in software engineering research, allowing them to develop future conclusions. © (2025), (Science and Information Organization). All Rights Res

关键词： Software design

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Historical Attack-Intensity-Based Event-Triggered Platoon Control of Connected Vehicles Under Actuator Failures and DoS Attacks

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 8052-8062页

作者： Lin, Huichao Dong, Jiuxiang Park, Ju H. Liaoning Province Key Laboratory of Safe Operation Technique for Autonomous Unmanned Systems College of Information Science and Engineering Shenyang110819 China Northeastern University State Key Laboratory of Synthetical Automation of Process Industries Shenyang110819 China Yeungnam University Department of Electrical Engineering Kyongsan38541 Korea Republic of

This paper considers the event-triggered (ET) platoon control of connected vehicles in the presence of actuator failures and DoS attacks. First, a historical attack-intensity-based ET mechanism is proposed to optimize communication resources. Compared with the existing event trigger mechanism, this mechanism utilizes not only the state error information but also historical attack intensity data to dynamically adjust the trigger threshold, which further conserves communication resources and enhances design flexibility in the case of DoS attacks. Next, a security platoon control scheme is designed to resist actuator faults and DoS attacks, and a delay switched system model is introduced to describe the vehicle platoon tracking error system. Then, a novel Lyapunov functional is developed and combined with switching techniques to establish sufficient conditions for the exponential stability of the tracking error system. Additionally, a co-design method of controller gain and event trigger parameters is proposed. Finally, simulation examples validate the superiority of the proposed historical attack-intensity-based ET platooning control scheme. © 1967-2012 IEEE.

关键词： Lyapunov functions

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