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Chinese Automation Congress (CAC)

作者： Xiongjun Wu Jialing Zhou Yuanlong Li Chunfang Chen Kai Li National Defense Key Laboratory of Science and Technology on Electromagnetic Scattering The 802 Institute of Shanghai Academy of Space Flight Technology The Eighth Academy of China Aerospace Science and Technology Corporation Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China School of Automation Nanjing University Science and Technology Nanjing The 802 Institute of Shanghai Academy of Space Flight Shanghai School of Automation Science and Electrical Engineering Beihang University Beijing

ISBN: (纸本)9781665426480

The constructive semi-global differential game concept is introduced into the multi-agent’s cooperative controller designing of typical autonomous unmanned systems subject to controller input constraint as well as the collision avoidance requirements simultaneously. The problem of driving each agent which is assume to subject to input constraint nonlinearity from the initial position to a desired one and at the same time avoiding collisions (referring to both static obstacles and other agents) is modeled and transformed into multi-agent’s collision avoidance problem. In view of the requirement that different agents working together might possibly have individual but conflicting purpose (such as in the multi-missile cooperative detection requiring slowly and continuing actions vs fast formation control scenario, and multi-agents’ fast arriving vs avoiding different kinds of obstacles). The differential game theory provided a mechanism or framework for investigating different kinds of problems in which several players seek to achieve individual purposes or goals, which might be competing rather than cooperation. In view of the input constraints, the problem is reduced as a semi-global differential game. Conditions are established to guarantee input constraints are satisfied, and mainly by using the Hamilton-Jacobi-Isaacs (HJI for short) PDIs and as well as ε-Nash equilibria. The semi-global property of the states are also guaranteed. It provides a description in terms of the invariant set for the overall differential game system under constraint controller input. Illustrative examples are carried out to verify the effectiveness of the method, and also the feasibility of the suggested control protocols.

关键词： Protocols Automation Design methodology Differential games Games Control systems Collision avoidance

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Non-Equilibrium Solidification Complexions in Additive Manufacturing Enable Exceptional Creep Resistance: An Example in Nickel-Based Superalloys

SSRN

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SSRN 2024年

作者： Li, Yansong Cui, Luqing Xu, Jinghao Xin, Tongzheng Jiang, Shuang Li, Yao Zhang, Honghong Dang, Xiaofeng Liang, Xiaoqing Gao, Shuang Mu, Yahang Lu, Kaiju Moverare, Johan J. He, Weifeng Shaanxi Xi’an710049 China School of Mechanical Engineering Xi’an Jiaotong University Shaanxi Xi’an710049 China Division of Engineering Materials Department of Management and Engineering Linköping University LinköpingSE-58183 Sweden School of Materials Science and Engineering Dalian University of Technology Dalian116024 China Key Laboratory of Electromagnetic Processing of Materials Ministry of Education Northeastern University Shenyang110819 China School of Materials Science and Engineering Chang’an University Shaanxi Xi’an710064 China School of Mechanical Engineering Xi’an Shiyou University Shaanxi Xi’an710065 China National Key Lab of Aerospace Power System and Plasma Technology Air Force Engineering University Shaanxi Xi’an710038 China School of Material Engineering Shanghai University of Engineering Science Shanghai201620 China Shenyang110016 China Defense Innovation Institute Academy of Military Science Beijing100071 China

Insufficient time-dependent properties at elevated temperatures, particularly creep resistance and ductility, are currently crucial factors impeding the use of additively manufactured Hastelloy X (HX). To address this limitation, a micro-nano olive-shaped carbide network was purposely introduced into HX via laser powder bed fusion (L-PBF) and following optimized heat treatment. The inherent chemical heterogeneity combined with the sufficient stored energy of boundaries, induced by the ultrafast cooling rate of the L-PBF process, creates favorable conditions for the formation of micro-nano precipitation networks. Compared to its untreated counterpart, the optimized HX exhibited considerably improved creep resistance, with an 83% increase in creep life and a 122% improvement in fracture ductility. Furthermore, through multiscale characterization techniques and theoretical calculations, the preferential precipitation behavior of the micro-nano carbide networks was systematically investigated from both kinetic and thermodynamic perspectives. The superior creep resistance of the L-PBF HX, decorated with carbide networks, stems from the synergistic effects of the higher cavity surface energy, greater pinning force for grain boundary sliding, and lower plasticity-assisted diffusion rate, which markedly inhibit the nucleation and growth of microvoids during high-temperature deformations. This work provides a comprehensive understanding of the strengthening mechanisms associated with non-equilibrium solidification-facilitated carbide networks, providing new insights into the targeted design and optimization of L-PBF alloys. © 2024, The Authors. All rights reserved.

关键词： Creep resistance

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A GMTI algorithm based on novel channel equalization method for multi-channel imaging radar

A GMTI algorithm based on novel channel equalization method ...

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IET International Radar Conference (IET IRC 2020)

作者： B. Pang S. Xing D. Dai Y. Li X. Wang National University of Defense Technology State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System Changsha China National University of Defense Technology College of Electronic Science Changsha China

For multi-channel SAR-GMTI system, the consistency between the channels is the indispensable condition for location and velocity measurement of ground moving targets. Therefore, particular attention should be paid to the study of channel equalization. However, traditional channel equalization methods often have the problems of low operating efficiency, large computational burden and poor adaptability, making them less effective. Aiming at this problem, the signal model for multi-channel SAR-GMTI processing is established. Based on this, a novel channel equalization method is proposed in this paper. The experimental results based on the measured data of airborne 7-channel SAR-GMTI system show that the proposed method can effectively eliminate the amplitude and phase error between channels without the need for iterative operation, thus improves the calculation efficiency and GMTI processing effect simultaneously.

关键词： radar imaging synthetic aperture radar equalisers iterative methods

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Ship Target Signature Indication based on Complex Signal Kurtosis in SAR Images

Ship Target Signature Indication based on Complex Signal Kur...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiangguang Leng Kefeng Ji Boli Xiong Gangyao Kuang State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and technology National University of Defense Technology Changsha China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Recently, complex signal kurtosis (CSK) is found to be a vital indicator of ship detection in synthetic aperture radar (SAR) images. Since CSK can be used as an indicator of ship detection, we consider it can also be used to indicate ship target signature. One of the basic rationales is that the higher the CSK is, the easier it is to be detected and thus the more obvious its characteristics are as a ship. Presence of sidelobes and defocusing are two common problems that affect the quality of ship targets. They are discussed in this paper from the perspective of CSK. Experimental results show that CSK can be used to indicate and improve ship quality. We believe that ship detection and recognition can benefit from the CSK indicator.

关键词： Marine vehicles Radar polarimetry Synthetic aperture radar Azimuth Remote sensing Random variables Spaceborne radar

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The Design of High-temperature Permanent Magnet Synchronous Motor based on Multi-physics Simulation

The Design of High-temperature Permanent Magnet Synchronous ...

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International Conference on Power Electronics and Motion Control (IPEMC)

作者： Yu Gao Zhenyang Hao Qiang Zhou Long Wang Yuqi Jia Wenjun Cui Yuliang Lu College of Automation Nanjing University of Aeronautics and Astronautics Nanjing China The Sixty-third Research Institute National University of Defense Technology Nanjing China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration AVIC Nanjing Engineering Institute of Aircraft System Nanjing China

ISBN: (数字)9781728153018

ISBN: (纸本)9781728153025

The development of power electronics technology has made it possible for all-electric combat vehicle (AECV). The high-voltage power supply system, high-temperature working environment and high power density requirements of AECV bring new challenges to the design of the permanent magnet synchronous motor (PMSM). In this paper, the electromagnetic design and thermal design of PMSM for AECV are taken as the research object. A high-speed PMSM with rated power of 1.5kW and rated speed of 18000r/min is designed. In order to accurately calculate the losses in the PMSM under the space vector pulse width modulation (SVPWM) voltage, this paper uses a multi-physics simulation method. Finally, electromagnetic simulation and thermal simulation of the motor are carried out. The results show that the motor meets the design requirements.

关键词： Space vector pulse width modulation Power system measurements Power supplies Permanent magnet motors Synchronous motors Power electronics Electromagnetics

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An adaptive fault detection strategy for Cz crystal growth process

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Mu, Lingxia Feng, Nan Zhang, Zhenhua Zhang, Youmin Zhang, Jian Xian University of Technology Crystal Growth Equipment and Systems Integration National Engineering Research Center Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada

The monitoring and fault detection for the Czochralski (Cz) crystal growth process is important to ensure the quality of the produced mono-crystalline silicon. The Cz process is a typical multi-modes industrial process, which makes the detection difficult in distinguish the change caused by the fault or mode switching. In this paper, an adaptive fault detection strategy for Cz crystal growth process is proposed. Firstly, quality-related variables are selected from numerous process variables, based on which the training dataset is constructed. Then, a fault detection model is built based on slowly-varying feature and statics indicator. A model switching strategy and updating algorithm are designed to handle the abnormal situation caused by the mode switching or fault occurrence. Three representative experiments are conducted to verify the performance of the proposed strategy, including numerical cases, a publicly available dataset, and Cz crystal growth process from our laboratory. © 1963-2012 IEEE.

关键词： Crystal growth from melt

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Comparison Study of Multitemporal PolSAR Classification Using Convolutional Neural Networks

Comparison Study of Multitemporal PolSAR Classification Usin...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chen-Song Tao Si-Wei Chen Shun-Ping Xiao State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System School of Electronic Science National University of Defense Technology Changsha China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Target classification is a main application of polarimetric synthetic aperture radar (PolSAR). With the PolSAR images of the same region observed on various dates, multitemporal classification plays an important role in crop discrimination and growth monitoring. However, due to the crop growth change, classification methods with good generalization are imperative. Recently, advanced deep learning techniques have achieved breakthroughs in optical image processing. Among them, convolutional neural networks (CNNs) can greatly improve accuracies in classification tasks. Because their multilayer architectures can extract the abstract feature with strong robustness to characterize the kinds' difference. In this vein, the multilayer architectures may be able to lead to the higher accuracies, as well as the better generalization in multitemporal PolSAR classification. So, this work aims to investigate multitemporal PolSAR classification using five CNNs of AlexNet, VGG16, Inception, ResNet50, and MobileNet. In detail, four roll-invariant features and two hidden features in the rotation domain are selected as inputs. Comparison experiment based on four temporal UAVSAR data with seven land covers validates the efficiency of these CNNs. For the train-used temporal, Inception can achieve the higher overall accuracies. While, for the train-not-used temporal, ResNet50 is with the better generalization.

关键词： Feature extraction Convolution Training Agriculture Convolutional neural networks Task analysis Veins

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Multi-label Classification with High-rank and High-order Label Correlations

arXiv

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arXiv 2022年

作者： Si, Chongjie Jia, Yuheng Wang, Ran Zhang, Min-Ling Feng, Yanghe Qu, Chongxiao The Chien-Shiung Wu College Southeast University Nanjing210096 China The MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai200240 China The School of Computer Science and Engineering Southeast University Nanjing210096 China Ministry of Education China School of Computing & Information Sciences Caritas Institute of Higher Education Hong Kong The Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education China The School of Mathematical Science Shenzhen University Shenzhen518060 China Shenzhen Key Laboratory of Advanced Machine Learning and Applications Shenzhen University Shenzhen518060 China The College of Systems Engineering National University of Defense Technology China The 52nd Research Institute of China Electronics Technology Group China

Exploiting label correlations is important to multi-label classification. Previous methods capture the high-order label correlations mainly by transforming the label matrix to a latent label space with low-rank matrix factorization. However, the label matrix is generally a full-rank or approximate full-rank matrix, making the low-rank factorization inappropriate. Besides, in the latent space, the label correlations will become implicit. To this end, we propose a simple yet effective method to depict the high-order label correlations explicitly, and at the same time maintain the high-rank of the label matrix. Moreover, we estimate the label correlations and infer model parameters simultaneously via the local geometric structure of the input to achieve mutual enhancement. Comparative studies over twelve benchmark data sets validate the effectiveness of the proposed algorithm in multi-label classification. The exploited high-order label correlations are consistent with common sense empirically. Our code is publicly available at https://***/Chongjie-Si/HOMI. Copyright © 2022, The Authors. All rights reserved.

关键词： Matrix algebra

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An Efficient Water Segmentation Method for SAR Images

An Efficient Water Segmentation Method for SAR Images

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Muchen Dai Xiangguang Leng Boli Xiong Kefeng Ji State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Engineering National University of Defense Technology Changsha China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Water segmentation is a fundamental step for the information processing of SAR image, which plays an important role in ship detection, disaster monitoring and other applications. Because of the complexity of scenario in the SAR images, water segmentation of SAR image is a challenging task. Fewer convolutional neural networks (CNNs) have been developed for SAR image water segmentation in recent years, the accuracy and speed of CNN for water segmentation can be further improved. In this paper, we established a SAR water segmentation dataset based on the GF3 satellite data. then an improved water segmentation network based on Bilateral Segmentation Network (BiSeNet) is proposed. Further we propose a loss function based on edge area and a novel training data generation method to improve the segmentation ability of the network. Experimental results based on water segmentation dataset show that the proposed segmentation method has better segmentation accuracy and speed.

关键词： Image segmentation Radar polarimetry Image edge detection Training data Training Synthetic aperture radar Marine vehicles

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Learning to Infer Weather States Using Partial Observations

Journal of Geophysical Research: Machine Learning and Comput...

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Journal of Geophysical Research: Machine Learning and Computation 2025年第1期2卷

作者： Jie Chao Baoxiang Pan Quanliang Chen Shangshang Yang Jingnan Wang Congyi Nai Yue Zheng Xichen Li Huiling Yuan Xi Chen Bo Lu Ziniu Xiao National Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric Physics Chinese Academy of Science Beijing China School of Atmospheric Sciences Chengdu University of Information Technology Chengdu China Key Laboratory of Mesoscale Severe Weather Ministry of Education and School of Atmospheric Sciences Nanjing University Nanjing China College of Computer National University of Defense Technology Hunan China Clustertech LTD Hong Kong China National Climate Center China Meteorological Administration Beijing China

Accurate state estimation of the high-dimensional, chaotic Earth's atmosphere marks a Sisyphean task, yet is indispensable for initiating weather forecasts and gauging climate variability. While much effort is devoted to assimilating observations and forecasts to infer weather states, the inherent low-dimensional statistical structure in atmospheric circulation, shaped by geophysical laws and geographic boundaries, is underutilized as an informative prior for state inference, or as reference for assessing representative of existing observations and planning new ones. We realize these potential by learning climatological distribution from climate reanalysis/simulation, using a deep generative model. For a case study of estimating 2 m temperature spatial patterns, the learned distribution faithfully reproduces climatology statistics. A combination of the learned climatological prior with few station observations yields strong posterior of spatial pattern estimates, which are spatially coherent, faithful and adaptive to observational constraints, and uncertainty-aware. This allows us to evaluate each observation's value in reducing pattern estimation uncertainty, and guide optimal observation network design by pinpointing the most informative sites. Our study showcases how generative models can extract and utilize information produced in the chaotic evolution of climate system. Deep generative model enables accurate spatial interpolation of weather variables from sparse observations The generative model produces spatially coherent and uncertainty-aware estimates, effectively constrained by observational data The approach provides a framework to quantify observation impact on uncertainty reduction, enabling optimization of observation networks Accurate estimation of weather conditions across a large area is crucial but challenging due to the complex and chaotic nature of the atmosphere. Traditional methods rely on combining observations with forecasts, which can be comp

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