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Model-Free Current Predictive control for PMSMs With Ultra-Local Model Employing Fixed-Time Observer and Extremum-Seeking Method

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IEEE Transactions on Power Electronics 2025年第8期40卷 10682-10693页

作者： Lin, Xinpo Liu, Jianxing Liu, Zhuang Gao, Yabin Peretti, Luca Wu, Ligang Harbin Institute of Technology Department of Control Science and Engineering Weihai264209 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China KTH Royal Institute of Technology Division of Electric Power and Energy Systems Stockholm10044 Sweden

Conventional model predictive current control of permanent magnet synchronous machines (PMSMs) relies heavily on a precise mathematical model, which may be challenging to obtain in certain cases. To address this issue, this paper proposes a model-free predictive current controller for PMSMs. Specifically, the dynamic model of the motor currents is represented using two ultra-local models, which express the derivatives of a controlled output as the sum of an amplified control input and an unknown offset term. All system parameters, nonlinear terms, and unmodeled dynamics are encapsulated into two offset terms. Online estimation of these two offset terms is performed using a second-order fixed-time convergence observer without requiring exact knowledge of the system parameters in advance. In contrast to both the linear extended state observer and the super-twisting observer, the fixed-time observer enhances convergence speed while concurrently sustaining minimal chatting. To get rid of the need for model rated parameters, an extremum-seeking approach is utilized to tune the control gains in the ultra-local model, where the amplitude of the disturbance item in extremum-seeking approach is adaptively attenuated, resulting in effective reduction of the fluctuations of both the control gains and PMSM's currents in steady state. Subsequently, a predictive controller is designed using this ultra-local model. Finally, the effectiveness and advantages of the proposed control scheme are confirmed through experimental results. © 1986-2012 IEEE.

关键词： Permanent magnets

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MM-UKAN++: A Novel Kolmogorov–Arnold Network-Based U-Shaped Network for Ultrasound Image Segmentation

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IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency control 2025年第4期72卷 498-514页

作者： Zhang, Boheng Huang, Haorui Shen, Yi Sun, Mingjian Harbin Institute of Technology Department of Control Science and Engineering Heilongjiang Harbin150001 China Pohang University of Science and Technology Department of Convergence IT Engineering Pohang37673 Korea Republic of Harbin Institute of Technology Suzhou Research Institute Jiangsu Suzhou215000 China Harbin Institute of Technology Department of Information Science and Engineering Shandong Weihai264200 China Harbin Institute of Technology Shandong Weihai264200 China Shandong Laboratory of Advanced Biomaterials and Medical Devices Shandong Weihai264209 China

Ultrasound (US) imaging is an important and commonly used medical imaging modality. Accurate and fast automatic segmentation of regions of interest (ROIs) in US images is essential for enhancing the efficiency of clinical and robot-assisted diagnosis. However, US images suffer from low contrast, fuzzy boundaries, and significant scale variations in ROIs. Existing convolutional neural network (CNN)-based and transformer-based methods struggle with model efficiency and explainability. To address these challenges, we introduce MM-UKAN++, a novel U-shaped network based on Kolmogorov-Arnold networks (KANs). MM-UKAN++ leverages multilevel KAN layers as the encoder and decoder within the U-network architecture and incorporates an innovative multidimensional attention mechanism to refine skip connections by weighting features from frequency-channel and spatial perspectives. In addition, the network effectively integrates multiscale information, fusing outputs from different scale decoders to generate precise segmentation predictions. MM-UKAN++ achieves higher segmentation accuracy with lower computational cost and outperforms other mainstream methods on several open-source datasets for US image segmentation tasks, including achieving 69.42% IoU, 81.30% Dice, and 3.31 mm HD in the BUSI dataset with 3.17 G floating point of operations (FLOPs) and 9.90 M parameters. The excellent performance on our automatic carotid artery US scanning and diagnostic system further proves the speed and accuracy of MM-UKAN++. Besides, the good performance in other medical image segmentation tasks reveals the promising applications of MM-UKAN++. The code is available on GitHub. © 1986-2012 IEEE.

关键词： Image segmentation

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Effects of La and Ce on the microstructure,thermal conductivity and strength synergy of the as-extruded Mg-Mn-RE alloys

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Journal of Magnesium and Alloys 2025年第2期13卷 654-667页

作者： Huafeng Liu Taiki Nakata Chao Xu Guangze Tang Danyang Li Xiaojun Wang Guisong Wang Shigeharu Kamado Lin Geng State Key Laboratory of Precision Welding&Joining of Materials and Structures Harbin Institute of TechnologyHarbin150001PR China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin150001PR China Department of Mechanical Engineering Nagaoka University of TechnologyNagaoka940-2188Japan Laboratory for Space Environment and Physical Sciences Harbin Institute of TechnologyHarbin150001PR China School of Physics Harbin Institute of TechnologyHarbin150001PR China

High thermal conductivity and high strength Mg-1.5Mn-2.5Ce alloy with a tensile yield strength of 387.0 MPa,ultimate tensile strength of 395.8 MPa,and thermal conductivity of 142.1 W/(m·K)was successfully fabricated via hot *** effects of La and Ce additions on the microstructure,thermal conductivity,and mechanical properties of the Mg-1.5Mn alloy were *** results indicated that both the as-extruded Mg-1.5Mn-2.5La and Mg-1.5Mn-2.5Ce alloys exhibited a bimodal grain structure,with dynamically precipitated nano-scaleα-Mn *** comparison with La,the addition of Ce enhanced the dynamic precipitation more effectively during hot extrusion,while its influence on promoting the dynamic recrystallization was relatively *** high tensile strength obtained in the as-extruded Mg-1.5Mn-2.5RE alloys can be attributed to the combined influence of the bimodal grain structure(with fine dynamic recrystallized(DRXed)grain size and high proportion of un-dynamic recrystallized(unDRXed)grains),dense nano-scale precipitates,and broken Mg12RE phases,while the remarkable thermal conductivity was due to the precipitation of Mn-rich phases from the Mg matrix.

关键词： Mg-Mn-RE alloys Thermal conductivity Mechanical properties Dynamic precipitation

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A Software Defect Prediction Method Using a Multivariate Heterogeneous Hybrid Deep Learning Algorithm

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Computers, Materials & Continua 2025年第2期82卷 3251-3279页

作者： Qi Fei Haojun Hu Guisheng Yin Zhian Sun College of Computer Science and Technology Harbin Engineering UniversityHarbin150001China Information Technology Research Department Jiangsu Automation Research InstituteLianyungang222062China School of Computer Science and Technology Harbin Institute of TechnologyShenzhen518055China

Software defect prediction plays a critical role in software development and quality assurance processes. Effective defect prediction enables testers to accurately prioritize testing efforts and enhance defect detection efficiency. Additionally, this technology provides developers with a means to quickly identify errors, thereby improving software robustness and overall quality. However, current research in software defect prediction often faces challenges, such as relying on a single data source or failing to adequately account for the characteristics of multiple coexisting data sources. This approach may overlook the differences and potential value of various data sources, affecting the accuracy and generalization performance of prediction results. To address this issue, this study proposes a multivariate heterogeneous hybrid deep learning algorithm for defect prediction (DP-MHHDL). Initially, Abstract Syntax Tree (AST), Code Dependency Network (CDN), and code static quality metrics are extracted from source code files and used as inputs to ensure data diversity. Subsequently, for the three types of heterogeneous data, the study employs a graph convolutional network optimization model based on adjacency and spatial topologies, a Convolutional Neural Network-Bidirectional Long Short-Term Memory (CNN-BiLSTM) hybrid neural network model, and a TabNet model to extract data features. These features are then concatenated and processed through a fully connected neural network for defect prediction. Finally, the proposed framework is evaluated using ten promise defect repository projects, and performance is assessed with three metrics: F1, Area under the curve (AUC), and Matthews correlation coefficient (MCC). The experimental results demonstrate that the proposed algorithm outperforms existing methods, offering a novel solution for software defect prediction.

关键词： Software defect prediction multiple heterogeneous data graph convolutional network models based on adjacency and spatial topologies CNN-BiLSTM TabNet

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Mode transitions in Hall effect thrusters by Varying duty ratio under pulsating operation

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Advances in Space Research 2025年第10期75卷 7466-7472页

作者： Ma, Haochen Zheng, He Liang, Tiance Li, Jiapeng Wei, Liqiu Han, Liang Li, Hong Ding, Yongjie School of Energy Science and Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China Key Laboratory of Aerospace Plasma Propulsion Ministry of Industry and Information Technology Harbin150001 China Beijing Institute of Control Engineering China Aerospace Science and Technology Corporation Beijing100089 China

During the operation of a Hall effect thruster, small changes in discharge voltage, mass flow, or magnetic field cause significant changes in the discharge mode of the thruster. Keeping other working conditions unchanged, the discharge mode of the Hall effect thruster can be triggered by changing the duty ratio. The experimental results show that at different frequencies, a small change in the duty ratio caused a significant increase in the discharge current and discharge oscillation amplitude. When the duty ratio changed from 70 % to 68 % at 90 kHz, the discharge mode changed from high- to low-oscillation mode. The discharge current oscillation decreased from 1.03 to 0.66, and the anode efficiency increased from 24.5 % to 25.8 %. When the duty ratio was changed from 64 % to 58 % at a pulse frequency of 70 kHz, the discharge current oscillation decreased from 1.26 to 0.85, and the anode efficiency increased from 23.5 % to 24.8 %. In the low-oscillation mode, the discharge current and anode voltage of the thruster were at the same frequency, and the discharge oscillation of the thruster was significantly reduced. Furthermore, the Faraday probe measurement results showed that the ion current density distribution of the thruster was more focused. The match between the supply of the working medium and the ionization rate improved the degree of ionization, leading to an improvement in thrust performance. Maintaining the Hall effect thruster in low-oscillation mode is of great significance for improving the reliability of the thruster. © 2025 COSPAR

关键词： Hall thrusters

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Coprime Factorization-Based Encryption and Attack Detection for Nonlinear Cyber-Physical Systems Using Deep Learning Approach

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IEEE Transactions on Automation science and engineering 2025年 22卷 14020-14029页

作者： Wu, Shimeng Luo, Hao Zhang, Jiusi Qiao, Xinyu Tian, Jilun Jiang, Yuchen Harbin Institute of Technology Department of Control and Simulation Center Harbin150001 China National Key Laboratory ofComplex System Control and Intelligent Agent Cooperation Harbin150001 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China

This paper presents a data-driven framework for integrating encryption transmission and attack detection in cyber-physical systems (CPS) with nonlinear physical plants. The main focus of this research is to use deep neural networks to realize the coprime factorization (CF) of nonlinear systems. The definition of the CF guides the network training and designing process, and the model’s topology is designed in the state-space form, which improves the interpretability of the data-driven CF. Based on the CF-aided neural networks, an encrypted transmission module is designed that projects information related to system dynamics into a perpendicular data space, which complements existing encryption methods from a control theory perspective. Subsequently, an anomaly detector are designed using the same CF pairs. This detector not only provides high-accuracy detection of attacks but also distinguishes between attacks and faults, thereby reducing the false positive rate and enhancing the reliability of the attack detection. The proposed method has been validated in a real CPS using a mecanum-wheeled vehicle as the physical plant, demonstrating its effectiveness and applicability. © 2004-2012 IEEE.

关键词： Factorization

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Robust Adaptive Sliding Mode Security control of Markov Jump Cyber-Physical Systems With Stochastic Injection Attacks Through Event-Triggered-Based Observer Approach

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3679-3692页

作者： Jiang, Baoping Niu, Fuzhou Wu, Zhengtian Qiu, Jianbin Suzhou University of Science and Technology School of Electronic and Information Engineering Suzhou215009 China Politecnico di Milano Department of Mechanical Engineering Milan20156 Italy Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

This article addresses the challenge of state observer design for sliding mode security control in Markov jump cyber-physical systems subjected to stochastic injection attacks. To enhance network efficiency, a dynamic event-triggered algorithm is introduced in the communication channel. First, the design begins with a Luenberger state observer featuring an adaptive compensator. This configuration aims to effectively counteract malicious attacks. Second, an integral sliding hyperplane is formulated within the estimation space, which serves as the foundation for deriving the sliding mode dynamics, ensuring robustness against disturbances. Recognizing the diversity of transition rates (TRs), an elastic sliding mode controller is designed to accommodate three distinct types of TRs, which is also strategically designed to guarantee reachability and maintain sliding motion. Third, stochastic stability with an H∞ attenuation level is conducted separately for each type of TR. Correspondingly, the development of an algorithm for determining threshold parameters in triggered conditions is presented. Simultaneously, a proof of the nonexistence of Zeno behavior is provided, ensuring the stability and efficiency of the proposed system. Finally, a simulation study using a practical model is included to empirically demonstrate the validity of the proposed method in a real-world context. © 2013 IEEE.

关键词： Stochastic systems

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Advancing antibiotic detection and degradation:recent innovations in graphitic carbon nitride(g-C_(3)N_(4))applications

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Journal of Environmental sciences 2025年第4期150卷 657-675页

作者： Rui Liu Chaojun Zhang Rijia Liu Yuan Sun Binqiao Ren Yuhang Tong Yu Tao Center of Pharmaceutical Engineering and Technology Harbin University of CommerceHarbin 150076China Institute of Advanced Technology Heilongjiang Academy of SciencesHarbin 150080China School of Environment Harbin Institute of TechnologyHarbin 150090China Materials Science and Physical Chemistry Department University of BarcelonaBarcelona 08028Spain State Key Laboratory of Urban Water Resource and Environment School of Civil&Environmental EngineeringHarbin Institute of Technology ShenzhenShenzhen 518055China

The uncontrolled release of antibiotics into the environment would be extremely harmful to human health and ***,it is in urgent need to monitor the environment and promote the detection and degradation of antibiotics to the relatively harmless by-products to a feasible *** carbon nitride(g-C_(3)N_(4))is a non-metallic n-type semiconductor that can be used for the antibiotic detection and degradation due to its easy synthesis process,excellent chemical stability and unique optical ***,the utilization of visible light,electron-hole recombination and electron conductivity have hindered its potential applications in the fields of photocatalytic degradation and electrochemical *** previous publications have highlighted the diverse modification methods for the g-C_(3)N_(4)-based materials,the underlying structure-performance relationships of g-C_(3)N_(4),especially for the detection and degradation of antibiotics,remains to be further *** view of this,the current review centered on the recent progress in the modification techniques of g-C_(3)N_(4),the detection and degradation of antibiotics using the g-C_(3)N_(4)-based materials,as well as the potential antibiotic degradation mechanisms of the g-C_(3)N_(4)-based ***,the underlying applications of the g-C_(3)N_(4)-based materials for antibiotic detection and degradation were also *** review would provide a valuable research foundation and the up-to-date information for the g-C_(3)N_(4)-based materials to combat antibiotic pollution in the environment.

关键词： g-C_(3)N_(4) Antibiotics Modification techniques Photocatalytic degradation Electrochemical detection

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Cross talk in full-color micro-LED displays

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Optics Letters 2025年第8期50卷 2530-2533页

作者： Lin, Yonghong Yin, Yanzhen Zhang, Fengchen Liu, Zhaojun Harbin Institute of Technology Harbin150001 China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China

To achieve full-color micro-LED displays using color conversion methods, the effects of three-color cross talk and blue-light cross talk on the color conversion layer were investigated. A light simulation was used to analyze the three-color cross talk caused by different pixel banks, comparing pixel banks made from ordinary photoresist and black photoresist. Various factors contributing to blue-light cross talk were also examined. The influence of the divergence angle of blue light and the structure of the color conversion layer for blue-light cross talk was analyzed through light simulations. Furthermore, potential solutions to mitigate blue-light cross talk were explored. © 2025 Optica Publishing Group.

关键词： Pixels

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Hyperbolic Sine Function-Based Full-State Feedback Attitude Tracking control for Rigid Spacecraft

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3412-3424页

作者： Dong, Rui-Qi Wu, Ai-Guo Li, Bin Duan, Guang-Ren Department of Automation Shenzhen518055 China Sichuan University School of Aeronautics and Astronautics Chengdu610207 China Southern University of Science and Technology Center for Control Science and Technology Shenzhen518055 China Harbin Institute of Technology Center for Control Theory and Guidance Technology Harbin150001 China

The attitude tracking control with unwinding-free performance for rigid spacecraft is studied in this article. A full-state feedback control law based on a hyperbolic sine function is developed such that the resulted closed-loop system can achieve two stable equilibria. By Lyapunov stability theory and Barbalat's Lemma, it is proven that the obtained closed-loop system is almost globally asymptotically stable, and achieves unwinding-free performance. Further, by constructing a strict Lyapunov function, it is demonstrated that the two stable equilibria are exponentially stable. Moreover, subsets of attraction regions corresponding to each stable equilibrium are characterized. The simulation results illustrate that the proposed attitude control scheme can effectively avoid the unwinding problem during attitude tracking. © 2025 IEEE.

关键词： Lyapunov functions

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