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9th IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2023

作者： Cui, Runhao Huang, Xucong Zhang, Peng Tang, Diyin Beihang University School of Automation Science and Electrical Engineering Beijing China Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9798350333794

Prognosis and health management (PHM) of control moment gyroscope (CMG) plays a crucial role in ensuring the operational efficiency and safety of spacecraft. In order to improve the accuracy of PHM and supplement abundant monitoring data, this paper proposes a digital twin-driven degradation modeling method, which establishes a detailed simulation model based on degradation mechanisms at the CMG component level. The digital twin model not only provides a large amount of high-quality data for performance evaluation, but also serves as an important reference for on-orbit CMG state assessment. Finally, a case of estimating virtual sensor degradation information based on reinforcement learning is used to demonstrate the effectiveness of the proposed digital twin method. © 2023 IEEE.

关键词： Gyroscopes

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Exact controllability of rational expectations model with multiplicative noise and input delay

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Journal of automation and Intelligence 2024年第1期3卷 19-25页

作者： Wenjing Wang Juanjuan Xu Huanshui Zhang Minyue Fu School of Control Science and Engineering Shandong UniversityJinan 250061China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future *** main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations *** particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free *** key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

关键词： Rational expectations model Exact controllability Exactly null controllability Multiplicative noise Input delay

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Analysis of light propagation characteristic in the aero-optic flow field of cone-headed vehicle with side window

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Optoelectronics Letters 2024年第1期20卷 58-64页

作者： XU Liang ZHOU Liye WANG Luyang ZHAO Shiwei WANG Tao Tianjin Key Laboratory of Complex Control Theory and Application School of Electrical Engineering and AutomationTianjin University of TechnologyTianjin 300384China School of Intelligent Engineering Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519000China

Aero-optic imaging deviation research is carried out for infrared-guided vehicle with cone-head side window,with a focus on the propagation characteristics of light in an aero-optic flow *** the light entering the aero-optic flow field from the free-stream should be close to the normal,numerous data indicate that the light is refracted away from the *** paper divides the aero-optic flow field into two parts and uses the gas density distribution in the aero-optic flow field to propose the hypothesis that there are two modes of refraction when light propagates through the flow *** results show that light propagates from the optically denser medium to the optically thinner medium after passing through the shock wave and eventually leads to refraction away from the normal when the light enters the aero-optic flow field.

关键词： flow propagation light

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Improvement of polypropylene/silicone rubber interface by insulating oils with pressure optimization

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IEEE Transactions on Dielectrics and Electrical Insulation 2025年第3期32卷 1289-1296页

作者： Luo, Zhaorui Chu, Jincheng Wang, Liyan Lu, Tianhe Tian, Zhengbing Li, Zhonglei Fang, Zhi Zhu, Xi Nanjing Tech University College of Electrical Engineering and Control Science Jiangsu Nanjing211816 China ZTT Cable Accessories Co. Ltd Jiangsu Nantong226010 China Tianjin University School of Electrical Automation and Information Engineering Tianjin300072 China

Cable accessory insulation system is inevitably affected by its interface states causing insulation failure. Insulating oils are often applied in the interface with a certain pressure to improve its performance, but the mismatching and degradation of polymer in insulating oils seriously affects the interface stability. This study focuses on polypropylene (PP) insulation and aims to improve its typical accessory interface with silicone rubber (SIR) by insulating oils with pressure. Results show that hydrocarbon oil has the biggest negative impact on PP with the most mass increment, more surface deposits and significant deteriorating in both mechanical and electrical properties. By contrast, appropriate absorption of Si-containing oil helps modify surface and fill initial defects of PP, promoting insulating performance. Furthermore, it is found that interface pressure is conductive to fabricate a stable PP/insulating oil/SIR structure with excellent insulating performance. However, excessive pressure causes a negative impact due to interface deformation of materials. Based on the analysis of interface microstructure and the calculation of contact stress between metal electrode and polymer, the mechanism of coupling interaction among polymer, insulating oil and external pressure is revealed. This research on the improvement of insulation interface can provide a key reference and basis for the manufacturing and optimizing of cable insulation. © 1994-2012 IEEE.

关键词： Silicone rubber

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Research on LSTM-based winding state prediction method 7

Research on LSTM-based winding state prediction method

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2024 7th International Conference on Power Electronics and control engineering, ICPECE 2024

作者： Wang, Yiyang Guo, Haifeng Li, Jianan Liu, Xinen Li, Xiang Du, Zhongbo Shen, Yang School of Electrical and Automation Engineering Liaoning Institute of Science and Technology Benxi117004 China Liaoning Province Robot Drive Control Engineering Laboratory Benxi117004 China

Mechanical and electrical equipment is widely used in various links of the manufacturing industry and is also the key to the implementation of modern industrial technology. Winding is the core component of transformers, electromagnetic valves, motors, robots, and other mechanical and electrical equipment. The safe and reliable operation of winding is the premise for the healthy operation of industrial equipment. Therefore, taking the core component of many industrial equipment, the winding, as the research object, and aiming to improve the safety and reliability of the equipment, this study focuses on the state prediction method of winding with the help of sensitive feature information. With the rapid development of industrial big data technology, data-driven technology, especially time series prediction technology, has developed rapidly. Considering the characteristics of winding degradation data, a winding state prediction method based on the Long Short-Term Memory (LSTM) approach is proposed. By using experimental data of winding, a health index reflecting their health status is constructed, and the LSTM is utilized for training the health index, thereby achieving time series-based state prediction of winding. This provides reliable support for the health status assessment of industrial mechanical and electrical equipment and enhances the reliability of the equipment. © Published under licence by IOP Publishing Ltd.

关键词： Machine windings

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Distributed Adaptive Coordination control for Autonomous Road Traffic at Multiple Intersections

Distributed Adaptive Coordination Control for Autonomous Roa...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Ji, Honghai Shi, Qirui Liu, Shida Fan, Lingling wang, Li School of Electrical and Control Engineering North China University of Technology Beijing100144 China School of Automation Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9789819639724

As societal demands on traffic control increase, traditional model-based traffic control methods are showing their limitations. This paper introduces a Distributed Adaptive Coordination control (DACC) algorithm, which integrates data-driven control and multi-agent systems, aimed at optimizing traffic signal control across multiple intersections to effectively balance queuing times. Through joint simulation experiments with SUMO and Python, and comparison with the Proportional-Integral-Derivative Coordination control (PIDCC) algorithm, the DACC algorithm has demonstrated advantages in reducing average queuing times and improving traffic flow efficiency. The results indicate that the DACC algorithm excels in managing traffic flow variations. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Traffic signals

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A Data-Driven Adaptive Optimal control with Input Saturation for Driverless Heavy-Duty Truck

A Data-Driven Adaptive Optimal Control with Input Saturation...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Ji, Honghai Yang, Jianfeng Liu, Shida Fan, Lingling Wang, Li School of Electrical and Control Engineering North China University of Technology Beijing100144 China School of Automation Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9789819639687

This paper mainly studies the longitudinal speed tracking problem of driverless heavy-duty trucks based on data-driven methods. A data-driven adaptive optimal control algorithm with control input saturation constraints is proposed in this paper to solve the problems of control input saturation and difficulty in establishing an accurate model in driverless heavy-duty truck systems. First, control constraints are added to the control input saturation problem of driverless heavy-duty trucks. Then, the dynamic linearization technology is used to model the nonlinear system of driverless heavy-duty trucks. After that, an appropriate index function is selected and the Newton-type optimization method is used to obtain the optimal controller. The method proposed in this paper only uses a small amount of input and output data and does not need to establish an accurate mathematical model. The simulation results show that compared with the PID algorithm, the proposed algorithm has advantages in speed tracking when applied to driverless heavy-duty truck systems. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Automobiles

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Prescribed-Time Stabilization of Singularly Perturbed Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 569-571页

作者： Yan Lei Yan-Wu Wang Xiao-Kang Liu Wu Yang the School of Artificial Intelligence and Automation Huazhong University of Science and Technology(HUST)Wuhan 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of EducationWuhan 430074China the School of Electrical Engineering Guangxi UniversityNanning 530004China

Dear Editor, This letter investigates the prescribed-time stabilization of linear singularly perturbed systems. Due to the numerical issues caused by the small perturbation parameter, the off-the-shelf control design techniques for the prescribed-time stabilization of regular linear systems are typically not suitable here. To solve the problem, the decoupling transformation techniques for time-varying singularly perturbed systems are combined with linear time-varying high gain feedback design techniques.

关键词： prescribed stabilization perturbed

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A WSN Node Fault Diagnosis Model Based on BRB with Self-Adaptive Quality Factor

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Computers, Materials & Continua 2023年第4期75卷 1157-1177页

作者： Guo-Wen Sun Gang Xiang Wei He Kai Tang Zi-Yi Wang Hai-Long Zhu School of Computer Science and Information Engineering Harbin Normal UniversitySongbei DistrictHarbin150025China Beihang University School of Automation Science and Electrical Engineering Beijing100191China Beijing Aerospace Automatic Control Institute Beijing100074China Rocket Force University of Engineering Xi’anShaanxi Province710025China

Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.

关键词： Self-adaptive quality factor belief rule base wireless sensor networks fault diagnosis

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Predicting the Bioaccessibility of Soil Cd,Pb,and As with Advanced Machine Learning for Continental-Scale Soil Environmental Criteria Determination in China

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Environment & Health 2024年第9期2卷 631-641页

作者： Kunting Xie Jiajun Ou Minghao He Weijie Peng Yong Yuan Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control School of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China School of Automation Guangdong University of TechnologyGuangzhou 510006China Health Risk Control School of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China

Investigating the bioaccessibility of harmful inorganic elements in soil is crucial for understanding their behavior in the environment and accurately assessing the environmental risks associated with *** batch experimental methods and linear models,however,are time-consuming and often fall short in precisely quantifying *** this study,using 937 data points gathered from 56 journal articles,we developed machine learning models for three harmful inorganic elements,namely,Cd,Pb,and *** thorough analysis,the model optimized through a boosting ensemble strategy demonstrated the best performance,with an average R2 of 0.95 and an RMSE of *** further employed SHAP values in conjunction with quantitative analysis to identify the key features that influence *** utilizing the developed integrated models,we carried out predictions for 3002 data points across China,clarifying the bioaccessibility of cadmium(Cd),lead(Pb),and arsenic(As)in the soils of various sites and constructed a comprehensive spatial distribution map of China using the inverse distance weighting(IDW)interpolation *** on these findings,we further derived the soil environmental standards for metallurgical sites in *** observations from the collected data indicate a reduction in the number of sites exceeding the standard levels for Cd,Pb,and As in mining/smelting sites from 5,58,and 14 to 1,24,and 7,*** research offers a precise and scientific approach for cross-regional risk assessment at the continental scale and lays a solid foundation for soil environmental management.

关键词： machine learning soil environmental criteria potentially harmful elements bioaccessibility sites

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