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Extinction Chains Reveal Intermediate Phases Between the Safety and Collapse in Mutualistic Ecosystems

engineering 2024年第12期43卷 89-98页

作者： Guangwei Wang Xueming Liu Ying Xiao Ye Yuan Linqiang Pan Xiaohong Guan Jianxi Gao Hai-Tao Zhang The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Digital Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China Guangdong HUST Industrial Technology Research Institute Huazhong University of Science and TechnologyDongguan 523808China Guangdong Provincial Engineering Technology Center of Autonomous Unmanned Vessels Dongguan 523808China MOE Key Laboratory of Intelligent Networks and Network Security&State Key Laboratory of Manufacturing Systems Xi’an Jiaotong UniversityXi’an 710049China Tsinghua National Laboratory of Information Science and Technology Department of AutomationTsinghua UniversityBeijing 100084China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA

Ecosystems are undergoing unprecedented persistent deterioration due to unsustainable anthropogenic human activities,such as overfishing and deforestation,and the effects of such damage on ecological stability are *** recent advances in experimental and theoretical studies on regime shifts and tipping points,theoretical tools for understanding the extinction chain,which is the sequence of species extinctions resulting from overexploitation,are still lacking,especially for large-scale nonlinear networked *** this study,we developed a mathematical tool to predict regime shifts and extinction chains in ecosystems under multiple exploitation situations and verified it in 26 real-world mutualistic networks of various sizes and *** discovered five phases during the exploitation process:safe,partial extinction,bistable,tristable,and collapse,which enabled the optimal design of restoration strategies for degraded or collapsed *** validated our approach using a 20-year dataset from an eelgrass restoration ***,we also found a specific region in the diagram spanning exploitation rates and competition intensities,where exploiting more species helps increase *** computational tool provides insights into harvesting,fishing,exploitation,or deforestation plans while conserving or restoring the biodiversity of mutualistic ecosystems.

关键词： Complex system Network science Overexploitation Regime shift Metastability

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Fault diagnosis of control moment gyroscope based on a new CNN scheme using attention-enhanced convolutional block

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Science China(Technological Sciences) 2022年第11期65卷 2605-2616页

作者： ZHAO HaoTian LIU Ming SUN YiYong CHEN Zhang DUAN GuangRen CAO XiBin Research Center of Satellite Technology School of AstronauticsHarbin Institute of TechnologyHarbin 150001China School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Department of Automation TsinghuaUniversityBeijing 100084China Control Theory and Guidance Technology School of AstronauticsHarbin Institute of TechnologyHarbin150001China

control moment gyroscope(CMG)is a typical attitude control system component for satellites and mobile robots,and the online fault diagnosis of CMG is crucial because it determines the stability and accuracy of the attitude control *** paper develops a data-driven CMG fault diagnosis scheme based on a new CNN *** this design,seven types of fault signals are converted into spectrum datasets through short-time Fourier transformation(STFT),and a new CNN network scheme called AECB-CNN is proposed based on attention-enhanced convolutional blocks(AECB).AECB-CNN can achieve high training accuracy for the CMG fault diagnosis datasets under different sliding window ***,simulation results indicate that the proposed fault diagnosis method can achieve an accuracy of nearly 95%in 1.28 s and 100%in 2.56 s,respectively.

关键词： fault diagnosis control moment gyroscope CNN scheme attention-enhanced convolutional block

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Finite-Time Synchronization of Flux-controlled Complex-Valued Memristive Neural Networks

Finite-Time Synchronization of Flux-Controlled Complex-Value...

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2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Wang, Yonghuan Wang, Leimin Wu, Genping China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

ISBN: (纸本)9798350316889

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time (wp, varpi, t) domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations. © 2023 IEEE.

关键词： Memristors

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Industrial control Anomaly Detection Based on Distributed Linear Deep Learning

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computers, Materials & Continua 2025年第1期82卷 1129-1150页

作者： Shijie Tang Yong Ding Huiyong Wang School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin541004China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyGuilin541004China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic TechnologyGuilin541004China Institute of Cyberspace Technology HKCT Institute for Higher EducationHong Kong999077China School of Mathematics&Computing Science Guilin University of Electronic TechnologyGuilin541004China

As more and more devices in Cyber-Physical Systems(CPS)are connected to the Internet,physical components such as programmable logic controller(PLC),sensors,and actuators are facing greater risks of network attacks,and fast and accurate attack detection techniques are *** key problem in distinguishing between normal and abnormal sequences is to model sequential changes in a large and diverse field of time *** address this issue,we propose an anomaly detection method based on distributed deep *** method uses a bilateral filtering algorithm for sequential sequences to remove noise in the time series,which can maintain the edge of discrete *** use a distributed linear deep learning model to establish a sequential prediction model and adjust the threshold for anomaly detection based on the prediction error of the validation *** method can not only detect abnormal attacks but also locate the sensors that cause *** conducted experiments on the Secure Water Treatment(SWAT)and Water Distribution(WADI)public *** experimental results show that our method is superior to the baseline method in identifying the types of attacks and detecting efficiency.

关键词： Anomaly detection CPS deep learning MLP(multi-layer perceptron)

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Periodic Tracking control for Linear Motor via Improved Terminal Sliding Mode control with Iterative Learning Disturbance Compensation

Periodic Tracking Control for Linear Motor via Improved Term...

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2022 Chinese automation Congress, CAC 2022

作者： Kang, Zhuang Liu, Zhitai Zhang, Zhongjin Li, Weinan Lin, Weiyang Wang, Zhifeng Harbin Institute of Technology Research Institute of Intelligent Control and Systems Harbin150001 China Engineering and Automation Foshan University School of Mechatronic Foshan China

ISBN: (纸本)9781665465335

This paper designs an improved fast nonsingular terminal sliding mode control (FNTSMC) method for permanent magnet linear motors to track the periodic control tasks, which uses an iterative learning controller to learn periodic information and improve the performance. By designing a non-singular terminal sliding surface and using Lyapunov stability theory, the FNTSMC is designed. Afterwards, with the help of the operator stability theory, the asymptotic convergence of the paper algorithm and the improvement of the tracking ability were strictly proved. Lastly, experiments on an actual linear motor setup illustrated the effectiveness and superior performance of the paper method. © 2022 IEEE.

关键词： Linear motors

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Digital Twin Model Design of Three-phase Inverter for Reliability Prediction 8

Digital Twin Model Design of Three-phase Inverter for Reliab...

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8th International Conference on Reliability of Electrical Products and Electrical Contacts, ICREPEC 2022

作者： Chen, Cen Sun, Chengzhi Zheng, Wei Zhang, Yuchen Xu, Yi Ye, Xuerong Zhai, Guofu Department of Electric Engineering and Automation Harbin Institute of Technology Harbin150001 China Beijing Aerospace Automatic Control Research Institute Beijing100089 China

ISBN: (纸本)9789881532374

Three-phase inverter is widely used in DC-AC power supply, motor drive, photovoltaic inverter, etc., whose reliability and stability are fundamental of efficient operation of various electrical systems. Digital twin technology can realize the life cycle performance analysis of the product by ingeniously combining data derived from multi-source and multi-level. Aiming at the reliability prediction, Saber, ANSYS and other software are used as carriers, and a 270V DC three-phase inverter is carried out to study the method of establishing the digital prototype model by integrating circuit models, behavior models and physical models. On this basis, taking DC/DC modules, diodes, MOSFETs, operational amplifiers, drivers as examples, the equivalent injection method of physics of failure models integrating performance degradation and functional failure is studied. Finally, a test method for products is researched to verify the validity and accuracy of the three-phase inverter digital twin model. © ICREPEC *** rights reserved

关键词： Digital devices

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MITD: A Multi-Dimensional Insider Threat Detection Framework Based On Deep Learning 17

MITD: A Multi-Dimensional Insider Threat Detection Framework...

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17th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2024

作者： Peng, Lijuan Feng, Jiaxuan Huang, Yuxin Zhou, Hongcheng Qin, Haoyang Qiu, Feng School of Computer Science and Technology Southwest University of Science and Technology Mianyang621010 China School of Mechanical Engineering and Vehicle Engineering Beijing Institute of Technology Beijing100081 China Automation Research Institute Co. Ltd. China South Industries Group Corporation Mianyang China

ISBN: (纸本)9798331507398

In this paper, we propose a multi-dimensional insider threat detection framework (MITD), which aims to improve the accuracy of detection by comprehensively analyzing user behavior patterns. We combine statistical features and behavioral sequences and use sequence pattern recognition, graph structure information mining, and adaptive feature extraction methods. It can reveal user behavior from multiple dimensions. Then, we intelligently fuse the extracted multi-dimensional features to generate a comprehensive feature representation. It is further fused with statistical features through two strategies: concat and bitwise addition. Experimental results based on the CERT r4.2 dataset show that the MITD framework significantly improves in terms of accuracy, precision, recall, and F1 score, reaching 93.2% accuracy and 93.5% recall. The results show that the MITD framework effectively improves the performance of insider threat detection and has great potential in practical applications. © 2024 IEEE.

关键词： Feature extraction

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Dynamic thermal coupling modeling and analysis of wet electro-hydrostatic actuator

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Chinese Journal of Aeronautics 2022年第6期35卷 298-311页

作者： Zongxia JIAO Yanpeng LI Tian YU Chaofan JIANG Ligang HUANG Yaoxing SHANG School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100083China Research Institute for Frontier Science Beihang University100083 BeijingChina Ningbo Institute of Technology Beihang UniversityNingbo 315800China

The electro-hydrostatic actuator(EHA)used in more electric aircraft(MEA)has been extensively studied due to its advantages of high reliability and high ***,this high integration results in a small heat dissipation area,leading to high-temperature ***,to reduce the temperature,a wet cooling method of using the pump leakage oil to cool the motor is adopted,which can also increase the difficulty of accurately predicting the system temperature in the early design *** solve this problem,a dynamic coupling thermal model of a wet EHA is proposed in this *** particular,the leakage oil of the pump is used as a coupling item between the electrical system and the hydraulic ***,an improved T-equivalent block model is proposed to address the uneven distribution of axial oil temperature inside the motor,and the control node method is applied to hydraulic system thermal ***,a dynamic coupling thermal model is developed that enables a dynamic evaluation of the wet EHA ***,experimental prototypes of wet motor and wet EHA are developed,while the temperature response of the wet motor at different rotation speeds and different loads and the temperature response of the wet EHA at no-load condition were verified experimentally at room temperature,*** maximum temperature difference between the experimental and theoretical results of the wet motor as well as the experimental and theoretical results of the wet EHA is less than 8℃.These test results indicate that the dynamic coupling thermal model is valid and demonstrate that the thermal coupling modeling method proposed in this paper can provide a basis for the detailed thermal design of EHA.

关键词： Electro-hydrostatic actuator Hydraulic More electric aircraft Thermal mode Wet motor

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Adaptive rapid defect identification in ECPT based on K-means and automatic segmentation algorithm

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Journal of Ambient Intelligence and Humanized Computing 2023年第11期14卷 1-18页

作者： Huang, Xuegang Yin, Chun Dadras, Sara Cheng, Yuhua Bai, Libing Hypervelocity Aerodynamics Institute China Aerodynamics Research and Development Center Mianyang621000 China School of Automation Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Electrical and Computer Engineering Department Utah State University LoganUT84321 United States

To enhance the detection efficiency in eddy current pulsed thermography, an adaptive feature extraction algorithm for defect identification is developed in this paper. The proposed algorithm involves four stages, namely, the thermal image segmentation, the variable interval search, the distance correlation clustering analysis and the between-class distance decision making. The transient thermal responses (TTRs) with similar characteristics are collected into one data block. The thermal image segmentation and variable interval search can help reduce the repetitive calculation in defect identification by choosing local optimums in each data block. The global optimum that has the largest sum of the between-class distance, is derived by first classifying the local optimums and then calculating the correlation distance of the thermal responses with the center points of each class. Finally, the TTRs with the largest between-class distance are regarded as the typical ones which can be used to identify the discriminative defect features of infrared image sequence. Finally, the comparison experiments are carried out to demonstrate the effectiveness and advantages of the proposed approach. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： K-means clustering

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Adaptive Nonsingular Terminal Sliding Mode control with Time-Delay Estimation for Linear Motor Systems

Adaptive Nonsingular Terminal Sliding Mode Control with Time...

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2022 Chinese automation Congress, CAC 2022

作者： Zhao, Yanqiu Liu, Zhitai Liu, Huanli Zhang, Zhongjin Lin, Weiyang Wang, Zhifeng Harbin Institute of Technology Research Institute of Intelligent Control and Systems Harbin150001 China Foshan University School of Mechatronic Engineering and Automation Foshan China

ISBN: (纸本)9781665465335

This paper presents a new adaptive nonsingualr terminal sliding mode control scheme for a class of motion platform driven by permanent-magnet linear motor. A barrier function (BF) is utilized to design the adaptive control gain law, then the overestimation of control gain that usually exists in sliding mode control (SMC) is avoided without requiring the upper boundary of system uncertainties. Moreover, this control scheme can guarantee the finite-Time convergence of the system and maintain the system state within a specified zero neighborhood. In addition, the practical time-delay estimation (TDE) technology is used to estimate the system dynamics and uncertainties, such as model errors, parameters variation and external disturbances. Therefore, the proposed controller has strong robustness and disturbance rejection ability. Finally, the effectiveness of this study is proved through some comparative experiments via a linear motor driven platform. © 2022 IEEE.

关键词： Sliding mode control

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