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IEEE information technology and Mechatronics Engineering Conference (ITOEC)

作者： Yaqiang Shi Jingyuan Bao Li Xu Zhenpo Tian Delie Ming National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China The Second Navy Representative Office Wuhan China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (数字)9781728143231

ISBN: (纸本)9781728143248

In scene matching, we use vector data instead of raster data to prepare a reference map. The BSP -algorithm is used to manage the vector data and then it is loaded on the aircraft. During the guidance process, reference maps are real-time prepared based on the track information and camera parameters. As the vector reference map is very different from the real-time map, conditional generation adversarial networks are used to convert the real-time map to a vector-style image and then match it to the vector reference map, which can achieve 86% matching accuracy.

关键词： Real-time systems Aircraft Cameras Buildings Generators Aircraft navigation Roads

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Enhanced gear fault diagnosis via heterodyne downconversion: Theoretical verification and optimized ultrasonic signal acquisition

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Measurement 2025年 256卷

作者： Jingchao Zhang Shaoqun Zhang Yixue Dong Chen Li Guoqian Jiang Yingwei Li Xiaoli Li School of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao 066004 China Intelligent Control System R&D Department Computer Application Technology Research Institute China Ordnance Industry Beijing 100089 China School of Electrical Engineering Yanshan University Qinhuangdao 066004 China School of Automation Science and Engineering South China University of Technology Guangzhou 510641 China Pazhou Lab Guangzhou 510330 China

Ultrasonic fault diagnosis has emerged as a promising technique for gear fault detection, owing to its capability to capture modulated high-frequency transients induced by incipient or localized defects. However, its practical application is constrained by the requirement for extremely high sampling rates. Heterodyne downconversion offers a potential solution by translating ultrasonic spectral components to lower frequencies, though its effectiveness in preserving diagnostic features remains insufficiently validated. This study conducts a theoretical analysis of the influence of heterodyne downconversion on ultrasonic signal characteristics and proposes an optimized heterodyne-based ultrasonic acquisition system with enhanced charge amplification and frequency conversion circuits. Experimental evaluations using a gear fault test platform demonstrate that the downconverted signals preserve the envelope spectral features of the original ultrasonic signals. Furthermore, comparative analyses indicate that the proposed method achieves superior fault detection sensitivity compared to conventional vibration-based techniques, particularly under high rotational speeds. These findings validate the feasibility and diagnostic advantages of the proposed heterodyne-based approach for efficient and accurate ultrasonic condition monitoring.

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Enhancing Adaptive Event-Triggered Protocols for Multi-Agent Consensus with External Disturbances

Enhancing Adaptive Event-Triggered Protocols for Multi-Agent...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Xianwei Li Yang Tang Bing Zhu Shaoyuan Li Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai China Seventh Research Division School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

This paper studies the design of adaptive event-triggered protocols for consensus of linear multi-agent systems (MASs) with external disturbances. Different from most of the existing results that deal with undirected graphs, this paper addresses directed graphs, specifically graphs that are assumed to be strongly connected. Inspired by a recent development [1], this paper devises novel adaptive event-triggered protocols for linear MASs with all agents subject to external disturbances. Two specific designs of composite triggering conditions are analysed and discussed. Compared with the disturbance-free case, additional constraints need to be introduced to deal with external disturbances and moreover the time-dependent terms are allowed to take any finite functions, rather than a class of L1 functions.

关键词： Protocols Eigenvalues and eigenfunctions Laplace equations Directed graphs Symmetric matrices Closed loop systems automation

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Guest Editorial:Advances in Bio-inspired Heuristics for Computing

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CAAI Transactions on Intelligence technology 2019年第3期4卷 127-128页

作者： XINCHAO ZHAO MAOGUO GONG XINGQUAN ZUO LINQIANG PAN School of Science Beijing University of Posts and TelecommunicationsBeijing 100876PR China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian UniversityXi’an 710071PR China School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876PR China Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of AutomationHuazhong University of Science and TechnologyWuhan 430074PR China

Bio-inspired computing (BIC), short for biologically inspired computing, is a field of study that loosely knits together subfields related to the topics of connectionism, social behaviour and emergence. The field of bio-inspired computing brings together researchers from many disciplines, including biology, computer science, mathematics, physics and genetics.

关键词： Guest Editorial Advances Bio-inspired Heuristics Computing

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AI-driven target screening and microfluidic sonication-assembled oral delivery of fucoxanthin-loaded probiotic vesicles for targeted alleviation of diet-induced obesity

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Chemical Engineering Journal 2025年 518卷

作者： Wang, Kuiyou Li, Xueqian Xu, Xiaoyu Chang, Jingru Sun, Mingyang Huang, Kexin Huang, Shasha Jiang, Hongyu Wang, Huihui Tan, Mingqian Su, Wentao State Key Laboratory of Marine Food Processing and Safety Control National Engineering Research Center of Seafood Dalian Polytechnic University Liaoning Dalian116034 China Dalian Key Laboratory for Precision Nutrition Academy of Food Interdisciplinary Science School of Food Science and Technology Dalian Polytechnic University Liaoning Dalian116034 China Collaborative Innovation Center of Seafood Deep Processing Dalian Polytechnic University Liaoning Dalian116034 China School of Mechanical Engineering and Automation Dalian Polytechnic University Liaoning Dalian116034 China School of Information Science and Engineering Dalian Polytechnic University Liaoning Dalian116034 China

Obesity is associated with numerous diseases, and its increasing prevalence poses serious public health challenges. Current pharmacological treatments, including appetite suppressants and fat absorption inhibitors, exhibit limited efficacy and adverse side effects. This study developed a Lactobacillus-derived vesicle (LCEV) system using microfluidic-assisted ultrasound technology to encapsulate fucoxanthin (Fx). In parallel, AI-based target screening was employed to evaluate its role in regulating lipid metabolism both in vitro and in vivo. Through simulation modeling and experimental validation, the microfluidic ultrasound technology generated a stable, uniformly distributed acoustic pressure field. It also optimized energy input and minimized localized high-pressure damage to vesicle structures, thereby enhancing encapsulation efficiency. In vitro, Fx-loaded LCEV (LCEV@Fx), assembled with microfluidic ultrasound, inhibited free fatty acid-induced lipid accumulation in liver cells, reduced oxidative stress, and suppressed adipocyte differentiation and lipid synthesis in 3T3-L1 preadipocytes. In vivo, vesicle encapsulation prolonged retention in the gastrointestinal tract, enhanced absorption across the serosal layer, and increased liver accumulation. AI-driven target screening and molecular docking analysis identified AMPKα1 as a key target for Fx in regulating lipid metabolism, providing a theoretical basis for its mechanism of action. Further experiments confirmed that LCEV@Fx reduced white adipose tissue accumulation and improved hepatic steatosis in HFD-induced mice. It promoted fatty acid oxidation through the AMPK/SIRT1 pathway while downregulating the expression of SREBP1 and FAS to inhibit lipid synthesis. Overall, this study, through AI-driven target screening and verification, clarified the mechanism of action of LCEV@Fx, providing new insights for its application in metabolic diseases, particularly demonstrating significant therapeutic potential in regul

关键词： Nutrition

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Energy Efficient Predictive control for Vapor Compression Refrigeration Cycle Systems

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IEEE/CAA Journal of Automatica Sinica 2018年第5期5卷 953-960页

作者： Xiaohong Yin Shaoyuan Li the School of Automation and Electronic Engineering Qingdao University of Science and TechnologyQingdao 266042China the Department of Automation Shanghai Jiao Tong Universityand the Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China

Abstract--Vapor compression refrigeration cycle （VCC） system is a high dimensional coupling thermodynamic system for which the controller design is a great challenge. In this paper, a model predictive control based energy efficient control strategy which aims at maximizing the system efficiency is proposed. Firstly, according to the mass and energy conservation law, an analysis on the nonlinear relationship between superheat and cooling load is carried out, which can produce the maximal effect on the system performance. Then a model predictive control （MPC） based controller is developed for tracking the calculated setting curve of superheat degree and pressure difference based on model identified from data which can be obtained from an experimental rig. The proposed control strategy maximizes the coefficient of performance （COP） which depends on operating conditions, in the meantime, it meets the changing demands of cooling capacity. The effectiveness of the control performance is validated on the experimental rig. Index Terms--Cooling load, model predictive control （MPC）, superheat, vapor compression refrigeration cycle （VCC）.

关键词： Cooling load model predictive control(MPC) superheat vapor compression refrigeration cycle(VCC)

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Quasi-synchronization of bounded confidence opinion dynamics with stochastic asynchronous rule

arXiv

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arXiv 2020年

作者： Su, Wei Wang, Xueqiao Chen, Ge Shen, Kai School of Automation and Electrical Engineering University of Science and Technology Beijing & Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing100083 China Beijing Key Laboratory of Information Service Engineering Beijing Union University Beijing100101 China National Center for Mathematics Interdisciplinary Sciences & Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Automation Beijing Institute of Technology Beijing100081 China

Recently the theory of noise-induced synchronization of Hegselmann-Krause (HK) dynamics has been well developed. As a typical opinion dynamics of bounded confidence, the HK model obeys a synchronous updating rule, i.e., all agents check and update their opinions at each time point. However, whether asynchronous bounded confidence models, including the famous Deffuant-Weisbuch (DW) model, can be synchronized by noise have not been theoretically proved. In this paper, we propose a generalized bounded confidence model which possesses a stochastic asynchronous rule. The model takes the DW model and the HK model as special cases and can significantly generalize the bounded confidence models to practical application. We discover that the asynchronous model possesses a different noise-based synchronization behavior compared to the synchronous HK model. Generally, the HK dynamics can achieve quasi-synchronization almost surely under the drive of noise. For the asynchronous dynamics, we prove that the model can achieve quasi-synchronization in mean, which is a new type of quasi-synchronization weaker than the "almost surely" sense. The results unify the theory of noise-induced synchronization of bounded confidence opinion dynamics and hence proves the noise-induced synchronization of DW model theoretically for the first time. Moreover, the results provide a theoretical foundation for developing noise-based control strategy of more complex social opinion systems with stochastic asynchronous rules. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

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Fault Diagnosis of SOFC Stack Based on Neural Network Algorithm

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Energy Procedia 2019年 158卷 1798-1803页

作者： Tao Xue Xiaolong Wu Yuanwu Xu Suwen Jing Zehua Li Jianhua Jiang Zhonghua Deng Xiaowei Fu Li Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430065 China

To realize the commercialization of SOFC, it must be ensured that it can work efficiently and stably. SOFC fault diagnosis becomes an essential part of the research. Due to the strong coupling of faults in the stack, this paper uses neural network algorithm to detect and diagnose faults. The simulation results verify that through the diagnosis of the test sample, the recognition rate of the test sample by the network is found to be 95%, which explains the neural network fault diagnosis model established in this paper on identifying the normal working state of the stack, the electrode stacking of the stack, and the gas leakage fault of the stack has good effectiveness and accuracy.

关键词： SOFC fault diagnosis neural network

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Structural Performance Analysis of Wall Climbing Robot 2

Structural Performance Analysis of Wall Climbing Robot

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2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and automation, AMIMA 2019

作者： Huang, Li Liao, Shangchun College of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan Hubei430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan Hubei430081 China

With the development of artificial intelligence technology, robotics technology has become more and more mature. Ground walking robots not only develop rapidly, but also have been applied in actual production and life. However, the development of wall climbing robot technology is still in the laboratory research and small-scale application. We live in a world where progress is continuing. Large-scale buildings, bridges and ships are becoming more and more common. In these places, it is inevitable to involve the construction, maintenance and clarity of high-rise buildings and ships. In the case of dangerous and inefficient manpower work, the application of wall climbing robots can play a very good role. Therefore, the development of wall climbing robots is of vital importance both now and in the future. Starting from the performance characteristics of wall climbing robot, this paper studies and summarizes the moving mode, control mode, conditions to be satisfied and various adsorption forms of wall climbing robot, and introduces the basic research situation in the field of wall climbing robot. © Published under licence by IOP Publishing Ltd.

关键词： Robot applications

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A New Intrusion Detection Method Based on Adaptive Feature Extraction

A New Intrusion Detection Method Based on Adaptive Feature E...

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第三十八届中国控制会议

作者： Ya-Li Wu Guo-Ting Li Yu-Long Fu Xiao-Peng Wang School of Automation and Information Engineering Xi'an University of Technology Shaanxi Province Key Laboratory of Complex System Control and Intelligent Information Processing

Compared with traditional machine learning, intrusion detection based on deep learning has the advantage of feature extraction. Auto-encoders, owing to having good feature extraction and dimensionality reduction ability, are known for the superior performance. However, the network structure selection is time-consuming and laborious. The essential features cannot be automatically extracted according to different distribution characteristics of the data set. Moreover, the existing data pre-processing method fails to adapt the model better. Based on the stack sparse auto-encoders(SSAE), we propose a new intrusion detection model named DBSO-SSAE. The algorithm is based on difference brain storm optimization(DBSO) which automatically adapts to selection network framework. Meanwhile, a new normalization strategy is introduced to further improve the accuracy of the model. The simulation results show that DBSO-SSAE greatly reduces the complexity of manual tuning and increases the adaptability of the network model.

关键词： intrusion detection feature extraction SSAE deep learning difference brain storm optimization

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