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学者姓名：王武
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Abstract ：
In this paper, a resilient adaptive covariance Kalman filter is developed for state estimation under false data injection attack (FDIA) during the process of measurements transmission. The extreme measurement deviation caused by unknown injection vectors is clipped by an adaptive saturation function, and an adaptive noise covariance matrix triggered by prediction residual is constructed to enhance the estimation performance and stability of the filtering error system under FDIA. To analyze the asymptotic convergence of the algorithm, the error expression is constructed to analyze the upper limit of prediction error. Finally, a simulation experiment on an inverted pendulum car verifies the stability and effectiveness of the proposed method in reducing the impact of unknown attack vectors.
Keyword ：
adaptive covariance adaptive covariance false data injection attack false data injection attack Kalman filter Kalman filter saturation function saturation function
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| GB/T 7714 | Zhang, Xiaoyun , Chai, Qinqin , Wang, Wu . Resilient adaptive covariance Kalman filter for state estimation under false data injection attacks [J]. | ASIAN JOURNAL OF CONTROL , 2025 . |
| MLA | Zhang, Xiaoyun 等. "Resilient adaptive covariance Kalman filter for state estimation under false data injection attacks" . | ASIAN JOURNAL OF CONTROL (2025) . |
| APA | Zhang, Xiaoyun , Chai, Qinqin , Wang, Wu . Resilient adaptive covariance Kalman filter for state estimation under false data injection attacks . | ASIAN JOURNAL OF CONTROL , 2025 . |
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针对"特种电机"课程里磁悬浮永磁电机的知识点复杂以致学生难于理解的问题,以3种飞轮储能用无轴承外转子无刷直流电机为研究对象,基于Ansys Maxwell有限元软件,设计了2个实验教学项目,包括磁场分布、空载磁链等基础内容,以及转矩与悬浮系统的耦合特性、悬浮力的提升措施等提升内容.通过仿真实验,可以帮助学生直观理解磁悬浮电机的本体结构和电磁特性等内容,提高学生对该课程的学习兴趣.调研结果表明,在参与调研的人数中,有96%以上的学生对实验项目很满意,该项目取得了较好的成效.
Keyword ：
有限元仿真实验教学 有限元仿真实验教学 特种电机 特种电机 飞轮磁悬浮无刷直流电机 飞轮磁悬浮无刷直流电机
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| GB/T 7714 | 严海龙 , 王武 , 钟天云 et al. 飞轮磁悬浮无刷直流电机仿真教学设计 [J]. | 电气电子教学学报 , 2025 , 47 (3) : 211-215 . |
| MLA | 严海龙 et al. "飞轮磁悬浮无刷直流电机仿真教学设计" . | 电气电子教学学报 47 . 3 (2025) : 211-215 . |
| APA | 严海龙 , 王武 , 钟天云 , 张文骞 , 李梦丽 . 飞轮磁悬浮无刷直流电机仿真教学设计 . | 电气电子教学学报 , 2025 , 47 (3) , 211-215 . |
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To address the issues of optimizing the operation of island electric-hydrogen coupled systems and high curtailment rates, a dispatch optimization strategy considering refined hydrogen energy modeling is proposed. The article analyzes the operational characteristics and electrolysis efficiency of alkaline electrolyzers and develops a refined model, balancing the economic and reliability aspects of the integrated energy system. An island integrated energy dispatch operation model is established. Case study results show that, compared to traditional electrolyzer models, the proposed model effectively reduces the number of start-stop cycles, extends the lifespan of the electrolyzer array, and enhances system economics. © 2025 IEEE.
Keyword ：
Economics Economics Electric load dispatching Electric load dispatching Electrolytic cells Electrolytic cells Hydrogen Hydrogen Optimization Optimization
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| GB/T 7714 | Meng, Chen , Lin, Qiongbin , Huang, Ruochen et al. Optimized scheduling of integrated energy systems on islands considering refined utilization of hydrogen energy [C] . 2025 : 1377-1382 . |
| MLA | Meng, Chen et al. "Optimized scheduling of integrated energy systems on islands considering refined utilization of hydrogen energy" . (2025) : 1377-1382 . |
| APA | Meng, Chen , Lin, Qiongbin , Huang, Ruochen , Liu, Ruirui , Wang, Wu . Optimized scheduling of integrated energy systems on islands considering refined utilization of hydrogen energy . (2025) : 1377-1382 . |
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The cascaded H-bridge inverter exhibits the characteristics of high voltage, large capacity and low harmonic distortion, and has a vital impact on application fields such as battery energy storage and photovoltaic power generation. Fault diagnosis of inverter switches is essential to enhancing equipment dependability. However, the limited number of fault samples and severe overlap of fault signals in real-word applications present difficulties for inverter fault diagnosis. In view of this, this paper introduces a hierarchical classification fault diagnosis strategy founded on an improved siamese network to achieve high-precision fault diagnosis. Firstly, for the purpose of addressing the issues of multiple fault categories and limited samples, an improved Siamese network based on long short-term memory and attention mechanism is proposed to extract more subtle fault difference features, thereby improving the recognition accuracy of overlapping fault classes. Then, to solve the problem of serious overlap of fault samples of different types in the preliminary grouping, a hierarchical fault diagnosis model is proposed to realize high precision fault diagnosis. Finally, the fault data of the cascaded H-bridge inverter was obtained through the semi-physical simulation platform to complete the diagnosis experiment. The experimental results demonstrate the recommended model offers clear benefits in terms of diagnostic accuracy when compared to the conventional model. © 2025 Institute of Physics Publishing. All rights reserved.
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| GB/T 7714 | Lin, Bin , Chai, Qinqin , Wang, Wu . Fault Diagnosis of Cascade H-bridge Inverter Based on Siamese Network under Small Sample Condition [C] . 2025 . |
| MLA | Lin, Bin et al. "Fault Diagnosis of Cascade H-bridge Inverter Based on Siamese Network under Small Sample Condition" . (2025) . |
| APA | Lin, Bin , Chai, Qinqin , Wang, Wu . Fault Diagnosis of Cascade H-bridge Inverter Based on Siamese Network under Small Sample Condition . (2025) . |
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Aiming at the problem that a large number of electric vehicles randomly connected to the grid poses a huge challenge to the security of the power grid, this paper proposes a strategy to guide the orderly charging of electric vehicles by using the time-of-use electricity price policy. Firstly, an orderly charging scheduling model for electric vehicles taking into account the response level to the policy is constructed. Then, a hybrid algorithm combining Spider Wasp Optimization (SWO) and Particle Swarm Optimization (PSO) is used to optimize the peak-valley electricity price period. Finally, by using the Monte Carlo and probability statistics theory methods to simulate the daily charging load of electric vehicles, the experiment of different response level are carried out. And results of different optimization methods for solving the scheduling model are compared. Comparison results show that the proposed method achieves the smallest peak to valley difference with the lest iterations. The proposed method can provides an effective strategy for peak shaving and valley filling. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Keyword ：
Mathematical programming Mathematical programming Monte Carlo methods Monte Carlo methods Particle swarm optimization (PSO) Particle swarm optimization (PSO)
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| GB/T 7714 | Lai, Qianling , Chai, Qinqin , Wang, Wu . Orderly Charging Optimization Scheduling for Electric Vehicles Based on Improved Spider Wasp Optimization [C] . 2025 : 118-126 . |
| MLA | Lai, Qianling et al. "Orderly Charging Optimization Scheduling for Electric Vehicles Based on Improved Spider Wasp Optimization" . (2025) : 118-126 . |
| APA | Lai, Qianling , Chai, Qinqin , Wang, Wu . Orderly Charging Optimization Scheduling for Electric Vehicles Based on Improved Spider Wasp Optimization . (2025) : 118-126 . |
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Solving the problem of water level fluctuations in small hydropower station systems is challenging under traditional industrial control methods. This difficulty arises from the system’s high nonlinearity and the complexities involved in mechanism modeling. To address this, an improved neuro-fuzzy approach is proposed. In which, the multi-head attention mechanism based long short-term memory network is used to describe complex water level change patterns, and the fuzzy controller is introduced to dynamically adjust the control parameters to reduce water level fluctuation. Simulation-based on real hydropower station system data is carried out, and the superiority of the improved model under complex dynamic conditions is verified by comparing the prediction accuracy of different neural network methods and the effects of fuzzy controller and traditional PID control. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Keyword ：
Control nonlinearities Control nonlinearities Fuzzy neural networks Fuzzy neural networks Proportional control systems Proportional control systems Three term control systems Three term control systems Two term control systems Two term control systems
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| GB/T 7714 | Yang, Rongguo , Chai, Qinqin , Cai, Fenghuang et al. Modeling and Control of Small Hydropower Stations Based on Neuro-Fuzzy Approach [C] . 2025 : 469-478 . |
| MLA | Yang, Rongguo et al. "Modeling and Control of Small Hydropower Stations Based on Neuro-Fuzzy Approach" . (2025) : 469-478 . |
| APA | Yang, Rongguo , Chai, Qinqin , Cai, Fenghuang , Wang, Wu . Modeling and Control of Small Hydropower Stations Based on Neuro-Fuzzy Approach . (2025) : 469-478 . |
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This paper proposes a leader-follower control method for multiple snake robot formation. Based on the simplified snake robot model, this work improves the traditional Serpenoid gait mode to a time-varying frequency form. Combined with the line-of-sight (LOS) method, a snake robot trajectory tracking controller is designed to enable the leader to track the desired trajectory at the ideal velocity. Then, the leader-follower following error system of a snake robot formation is established. In this framework, the follower can maintain a preset geometric position relationship with the leader to ensure the fast convergence of the formation location. Lyapunov's theory proves the stability of a snake robot formation error. Simulation and experimental results show that this strategy has the advantages of faster convergence speed and higher tracking accuracy than other current methods.
Keyword ：
Formation control Formation control Leader-follower Leader-follower Snake robot Snake robot Trajectory tracking Trajectory tracking
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| GB/T 7714 | Wang, Wu , Du, Zhihang , Li, Dongfang et al. Leader-follower method-based formation control for snake robots [J]. | ISA TRANSACTIONS , 2025 , 156 : 609-619 . |
| MLA | Wang, Wu et al. "Leader-follower method-based formation control for snake robots" . | ISA TRANSACTIONS 156 (2025) : 609-619 . |
| APA | Wang, Wu , Du, Zhihang , Li, Dongfang , Huang, Jie . Leader-follower method-based formation control for snake robots . | ISA TRANSACTIONS , 2025 , 156 , 609-619 . |
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Background: Traditional temperature-dependent models face difficulties in compact systems due to complex temperature control. This study introduces an electric field strength and runtime driven (E-t) band model to improve GE performance by correlating band behavior with electric field and runtime rather than temperature. Results: We developed a compact E-t model based GE system, which equipped with inert platinum-titanium electrodes, a quartz-glass-embedded tank for passive cooling, and smartphone-based real-time fluorescence imaging. Experimental results from real-time tracking of GE bands, model fitting under different E-t conditions, and the separation of rice receptor protein kinase genes (CERK1 and CEBiP) confirmed that the proposed model can accurately describe electrophoretic band migration and dispersion, while maintaining good agreement with traditional temperature-based models and being little affected by temperature. Furthermore, successful nucleic acid separation was achieved within minutes under a high electric field strength in our system. Significance: By minimizing the reliance on temperature control mechanisms, the E-t band model offers a new perspective for the design of analytical chemistry instruments, enabling electrophoresis to focus primarily on optimizing the two key parameters, E and t. In addition, our portable, real-time imaging GE system enhances separation efficiency and provides a practical, high-performance reference solution for rapid, on-site analysis applications.
Keyword ：
Band dispersion Band dispersion Band model Band model Gel electrophoresis (GE) Gel electrophoresis (GE) Joule heat Joule heat Nucleic acid separation Nucleic acid separation Real-time imaging Real-time imaging
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| GB/T 7714 | Luo, Kan , Chen, Yu , Liang, Chaobing et al. An electric field and runtime driven band model for high-speed, real-time imaging gel electrophoresis [J]. | ANALYTICA CHIMICA ACTA , 2025 , 1350 . |
| MLA | Luo, Kan et al. "An electric field and runtime driven band model for high-speed, real-time imaging gel electrophoresis" . | ANALYTICA CHIMICA ACTA 1350 (2025) . |
| APA | Luo, Kan , Chen, Yu , Liang, Chaobing , Zhang, Qirong , Huang, Jing , Wang, Wu et al. An electric field and runtime driven band model for high-speed, real-time imaging gel electrophoresis . | ANALYTICA CHIMICA ACTA , 2025 , 1350 . |
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Background: Slab gel electrophoresis (SGE) remains fundamental to biomedical research but faces limitations for point-of-care testing due to its large footprint, operational inefficiencies, and lack of real-time imaging capabilities. Methods: We developed a portable, real-time imaging SGE system featuring a compact and modular design. The system integrates a 3D-printed SGE tank with embedded quartz glass plates that facilitate fluorescence imaging and efficient heat dissipation, ensuring stable operation under high electric fields without significant temperature rise. A uniform LED panel provides consistent, high-quality excitation, while a smartphone-based detection module with an optical filter enables real-time monitoring of fluorescent bands across a large imaging area (100 x 60 mm(2)). Results: The SGE system offers efficient passive heat dissipation and enables sensitive fluorescence-based DNA detection, with a detection limit as low as 0.07 ng/mu L and a linear range of 0.08-10.00 ng/mu L. It supports a throughput of 12 samples per run. Its compact size (108 x 108 x 60 mm(3)), light weight (0.7 kg), and low cost (similar to $65) ensure both portability and affordability. We have successfully applied the prototype to screen genes (CERK1 and CEBiP), achieving a reduced electrophoresis runtime of 12 min at 100 V while enabling real-time band tracking. Significance: Our portable SGE system addresses critical limitations of traditional systems through its integrated design, large imaging area, high efficiency, and cost effectiveness. The open source platform enables both accessibility in developing regions and extensibility to diverse molecular detection applications. The established engineering approaches offer a generalizable reference for developing similar devices.
Keyword ：
DNA analysis DNA analysis Fluorescence-based detection Fluorescence-based detection Portable system Portable system Real-time imaging Real-time imaging Slab gel electrophoresis (SGE) Slab gel electrophoresis (SGE)
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| GB/T 7714 | Luo, Kan , Chen, Yu , Fan, Min et al. A portable, low-cost real-time imaging slab gel electrophoresis system for rapid separation of nucleic acids [J]. | SENSORS AND ACTUATORS B-CHEMICAL , 2025 , 440 . |
| MLA | Luo, Kan et al. "A portable, low-cost real-time imaging slab gel electrophoresis system for rapid separation of nucleic acids" . | SENSORS AND ACTUATORS B-CHEMICAL 440 (2025) . |
| APA | Luo, Kan , Chen, Yu , Fan, Min , Li, Jianxing , Wang, Wu . A portable, low-cost real-time imaging slab gel electrophoresis system for rapid separation of nucleic acids . | SENSORS AND ACTUATORS B-CHEMICAL , 2025 , 440 . |
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Advanced wind power prediction technique plays an essential role in the stable operation of the grid with largescale grid integration of wind power. Most research focuses on distance-based static classification where the subjective nature of initial center selection increases the uncertainty of the prediction. And the data classification on a daily basis neglects the potentially significant climate changes at smaller time scales. To address these issues, the improved snake optimization-long short-term memory (ISO-LSTM) model with Gaussian mixture model (GMM) clustering is proposed to forecast wind power from an adaptive perspective. By exploiting the merits of the probabilistic classification, the K-means optimized GMM clustering enables an appropriate feature modelling for substantial climate changes at smaller time scales. Then the ISO algorithm exhibits higher search accuracy and is better suited for finding hyperparameter combinations for LSTM neural networks. The data from the National Aeronautics and Space Administration (NASA) of the US is used to validate the effectiveness of the proposed method. Compared to the traditional K-means clustering, the K-means optimized GMM clustering has increased accuracy by 2.63 %. Simultaneously, with the adoption of the enhanced ISO algorithm, the accuracy further increases by 7.27 %. Different existing models have also been tested; it shows that the proposed model demonstrates higher prediction accuracy.
Keyword ：
Gaussian mixture model Gaussian mixture model Improved snake optimization Improved snake optimization K -means algorithm K -means algorithm Long short-term memory network Long short-term memory network Probabilistic classification Probabilistic classification
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| GB/T 7714 | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin et al. Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty [J]. | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
| MLA | Zhou, Yu et al. "Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty" . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 157 (2024) . |
| APA | Zhou, Yu , Huang, Ruochen , Lin, Qiongbin , Chai, Qinqin , Wang, Wu . Probabilistic optimization based adaptive neural network for short-term wind power forecasting with climate uncertainty . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
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