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SSRN 2024年

作者： Li, Weichen Zhao, Jieliang Wu, Xiangbing Liang, Lulu Wang, Wenzhong Yan, Shaoze School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China Division of Intelligent and Biomechanical Systems State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical Engineering Tsinghua University Beijing100084 China

Efficient and stable heat dissipation structure is crucial for improving the convective heat transfer performance of thermal protection system (TPS) for hypersonic aircrafts. However, the heat dissipation wall of the current TPS is limited by a single material and structure, inefficiently dissipating the large amount of accumulated heat generated during the high-speed maneuvering flight of hypersonic aircraft. Here a convection cooling channel structure of TPS is proposed, which is an innovative multi-level structure inspired by the natural honeycomb. An active cooling channel (PCM-HC) is designed by using a variable-density topology optimization method and filled with phase change material (PCM). Numerical simulations are used to investigate the thermal performance of the PCM-HC wall, focusing on the influence of PCM properties, structural geometric parameters and PCM types on the heat transfer characteristics. The results demonstrate that the honeycomb-like convection cooling channel wall, combined with PCM latent heat of phase change, exhibits superior heat dissipation capability. With a heat flux input of 50 kW/m2, the maximum temperature on the inner wall of PCM-HC is reduced by 12 K to 20 K. Different PCMs have opposing effects on heat transfer performance due to their distinct thermophysical properties. This work can provide a theoretical basis for the design of high-efficiency cooling channel, improving the heat dissipation performance in the TPS of hypersonic aircraft. © 2024, The Authors. All rights reserved.

关键词： Honeycomb structures

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Optimal Tracking Performance of Networked Control systems Under DoS and its Applications

Optimal Tracking Performance of Networked Control Systems Un...

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Chinese Automation Congress (CAC)

作者： Xinyu Ren Bo Li Feng Zhao Xiangyong Chen Xianhe Zhang Xiaowei Jiang Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Wuhan China School of Finance Anhui University of Finance and Economics Bengbu China Key Laboratory of Complex systems and Intelligent Computing Universities of Shandong Linyi University Linyi China Key Laboratory of Complex systems and Intelligent Computing School of Automation and Electrical Engineering Universities of Shandong Linyi University Linyi China School of Electrical Engineering and Automation Hubei Normal University Huangshi China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

This paper investigates the optimal tracking performance (OTP) of multiple-input multiple-output (MIMO) discrete networked control systems (NCSs) under the influence of Denial of Service (DoS) attack, channel noise, and bandwidth constraints. The channel noise is assumed to be additive Gaussian white noise (AWGN). Due to the randomness of DoS attack, a Bernoulli distribution is used for DoS modeling. Utilizing frequency domain analysis methods, coprime factorization, all-pass decomposition, and Youla parameterization, an explicit expression for the optimal tracking performance (OTP) of the system under the two-degree-of-freedom (TDOF) controller is derived. The analysis indicates that non-minimum phase (NMP) zeros, unstable poles (UPs), DoS attack, and network constraints affect the OTP of NCSs. Finally, the theoretical results are validated through simulations of MIMO NCS and vehicle control system.

关键词： Automation Networked control systems Frequency-domain analysis Bandwidth Interference White noise Cyber-physical systems Poles and zeros MIMO communication Multi-agent systems

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Torque Ripple Minimization Approach of a 3-phase Switched Reluctance Motor

Torque Ripple Minimization Approach of a 3-phase Switched Re...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Zeineb Touati Imed Mahmoud Adel Khedher LATIS- Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Ecole Nationale d'Ingénieurs de Sousse Sousse Tunisie Institut Supérieur des Sciences Appliquées et de Technologie de Mahdia Université de Sousse Ecole Nationale d'Ingénieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Monastir Mahdia Tunisie Ecole Nationale d'Ingénieurs de Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Sousse Tunisie

ISBN: (纸本)9781665414937;9781665430579

A major problem in Switched Reluctance Motor (SRM) is torque ripple. This latter causes undesirable acoustic noise and vibration. Thus, to attenuate the oscillations amplitudes, we propose solutions exploiting the Indirect Instantaneous Torque Control (IITC) and considering the speed and load variations are proposed in this article. Using the simulation results provided by the execution of the behavioral model developed based on the finite element method, we determine the SRM static and dynamic characteristics. The proposed method efficiency is also demonstrated and verified through simulations.

关键词： Vibrations Torque Simulation Torque control Switches Switched reluctance motors Finite element analysis

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Predefined-Time Synchronization of Inertial Memristive Neural Networks

Predefined-Time Synchronization of Inertial Memristive Neura...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Zeng, Kan Wang, Leimin School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

ISBN: (纸本)9781665412872

This article investigates the predefined-time synchronization (PTS) of inertial memristive neural networks (IMNNs). First, we reduce the order of the system and design an effective controller for the error system. Furthermore, several new criteria for PTS of IMNNs are obtained and a user-defined settling time is provided. Lastly, the effectiveness of the results is proved by simulation experiment. © 2021 IEEE.

关键词： Synchronization

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Survival prediction of LGG patients based on deep learning of MRI data and genomic data integration

Survival prediction of LGG patients based on deep learning o...

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2021 China Automation Congress, CAC 2021

作者： Sun, Lingzhi He, Yong School of Automation 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 Wuhan430074 China

ISBN: (纸本)9781665426473

Low-grade gliomas (LGG) is the most common primary intracranial tumor, with high incidence rate, high recurrence rate, high mortality rate and low cure rate. Therefore, it is necessary to predict the survival of LGG patients in diagnosis. Considering the complementarity of information, the new proposed algorithm in this study is designed to integrate Magnetic Resonance Image (MRI) data and gene expression data using deep learning method to predict the Disease Specific Survival (DSS) of LGG patients. Firstly, MRI data of 44 patients is screened from TCIA database, and then the corresponding gene expression data of 44 patients is searched from TCGA database. Then, 724 image feature data extracted from MRI data are filtered and extracted by deep learning method, and DSS tags are used to train the model;deep learning method is used to extract 20530 features of gene expression data, and DSS tags are also used for training. As a contrast, the deep learning method is used to integrate the two features to train the model. Experiments are evaluated on MRI data, gene expression data and the integration data of MRI and gene expression data, respectively. The results show that by using the integration of MRI data and gene expression data performs better than using single data in terms of the time-dependent receiver operating characteristic(ROC) and the area under the curve (AUC) of the ROC curve criteria. © 2021 IEEE

关键词： Magnetic resonance imaging

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Enhancing Boundary Segmentation for Topological Accuracy with Skeleton-based Methods

arXiv

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arXiv 2024年

作者： Liu, Chuni Ma, Boyuan Ban, Xiaojuan Xie, Yujie Wang, Hao Xue, Weihua Ma, Jingchao Xu, Ke Collaborative Innovation Center of Steel Technology Beijing Advanced Innovation Center for Materials Genome Engineering School of Intelligence Science and Technology Shunde Innovation School Institute for Advanced Materials and Technology Key Laboratory of Intelligent Bionic Unmanned Systems University of Science and Technology Beijing Beijing100083 China Institute of Materials Intelligent Technology Liaoning Academy of Materials Shenyang110004 China School of Materials Science and Technology Liaoning Technical University Liaoning 114051 China

Topological consistency plays a crucial role in the task of boundary segmentation for reticular images, such as cell membrane segmentation in neuron electron microscopic images, grain boundary segmentation in material microscopic images and road segmentation in aerial images. In these fields, topological changes in segmentation results have a serious impact on the downstream tasks, which can even exceed the misalignment of the boundary itself. To enhance the topology accuracy in segmentation results, we propose the Skea-Topo Aware loss, which is a novel loss function that takes into account the shape of each object and topological significance of the pixels. It consists of two components. First, a skeleton-aware weighted loss improves the segmentation accuracy by better modeling the object geometry with skeletons. Second, a boundary rectified term effectively identifies and emphasizes topological critical pixels in the prediction errors using both foreground and background skeletons in the ground truth and predictions. Experiments prove that our method improves topological consistency by up to 7 points in VI compared to 13 state-of-art methods, based on objective and subjective assessments across three different boundary segmentation datasets. The code is available at https://***/clovermini/Skea topo. Copyright © 2024, The Authors. All rights reserved.

关键词： Pixels

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Short-term power load forecasting during the COVID-19 pandemic using XGBoost and Copula theory

Short-term power load forecasting during the COVID-19 pandem...

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2021 China Automation Congress, CAC 2021

作者： Liu, Bo-Wen Xu, Da He, Yong School of Automation 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 Wuhan430074 China

ISBN: (纸本)9781665426473

The global coronavirus disease (COVID-19) has brought great challenges to the power systems due to its limitations on social, economic and productive activities. This paper proposes a short-term load forecasting method during COVID-19 pandemic based on copula theory and eXtreme Gradient Boosting (XGBoost). In this method, the coupling relationship among the cross-domain meteorological, public health, and mobility time-series data are fully analyzed based on copula theory, which is used for the short-term power load forecasting based on multi-factor fusion XGBoost algorithm. The proposed method has been fully evaluated and benchmarked on available cross-domain open-access United States data to demonstrate its effectiveness and superiority on short-term load forecasting of COVID-19. © 2021 IEEE

关键词： COVID-19

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Uniform Stability of Fractional-order Memristive Neural Networks with Hybrid Time-Varying Delays

Uniform Stability of Fractional-order Memristive Neural Netw...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Hu, Xiaofang Wang, Leimin School of Automation 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 Wuhan430074 China

ISBN: (纸本)9781665412872

This article discusses the uniform stability of Caputo fractional-order memristive neural networks (FMNNs) with discrete delay and distributed delay. By virtue of fractional-order Razumikhin-type theorem, interval matrix method, differential inclusion and set-valued mapping, a LMI-based standard is acquired to certify uniform stability of the addressed FMNNs. Lastly, the validity of the constructed criterion is manifested by an example. © 2021 IEEE.

关键词： Time delay

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Stabilization of discrete time stochastic linear systems with time delay via event-triggered control

Stabilization of discrete time stochastic linear systems wit...

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2021 China Automation Congress, CAC 2021

作者： Dong, Jian Zong, Xiaofeng School of Automation 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 Wuhan430074 China

ISBN: (纸本)9781665426473

This paper presents the stabilization problem of a class of discrete-time stochastic linear systems with time delay using an event-triggered control(ETC) strategy. For the general linear systems, we propose a new event triggering mechanism and deduce sufficient conditions for mean square exponentially stabilizability(MSES) and almost sure exponentially stabilizability(ASES) via ETC. The results show that the stability of the system depends on the system parameters (time delay, noise, event trigger threshold parameter, and unstable characteristic value of the original system). When the feedback control is disturbed by low-intensity noise, the unstable system can be stable in the mean square. Finally, the validity of the theoretical results is illustrated through a simulation example. © 2021 IEEE

关键词： Linear systems

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Dynamic analysis and control of fractional order memristor Hopfield neural network

Dynamic analysis and control of fractional order memristor H...

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第42届中国控制会议

作者： Feng Liu Gang Cai Feifan Zhou Wei Wang Hua Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network(fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system.

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