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第41届中国控制会议

作者： Gang Li Xiaowei Jiang Le You Xianhe Zhang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education School of Electrical Engineering and Automation Hubei Normal University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This work looks into the quantized impulsive consensus challenges of nonlinear leader-following multi-agent *** graph theory,principle of differential dynamics,logarithmic quantizer,matrix theory,and the Lyapunov function,among other things,are used to investigate the key discoveries on *** appropriate consensus protocols which contain quantized all agents' relative state information and quantized a part of agents' relative state *** the sake of reducing communication consumption and energy,we combine two control strategies and design two control protocols according to the characteristics of quantized control and impulsive *** a series of deductions,we find that under quantized impulsive control,multi-agent systems can achieve consensus as long as certain sufficient conditions are ***,the simulation example demonstrates the validity and correctness of this papers theoretical approach.

关键词： Multi-agent systems Leader-following Quantized impulsive consensus

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Detection of Termite Nests in Dams Using Ground Penetrating Radar Based on Deep Learning 20

Detection of Termite Nests in Dams Using Ground Penetrating ...

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20th International Conference on Ground Penetrating Radar, GPR, 2024

作者： Peng, Jiao Xue, Wei Wang, Wenkai Song, Junlei Zhou, Feng Huang, Pengchun Zhang, Zhixuan Zhang, Feng Zhang, Xu Chen, Longjia Sun, Li School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China Dam Safety Monitoring and Termite Control Center of Hubei Provincial Department of Water Resources China Key Laboratory of Termite Control Ministry of Water Resources China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

Termites have always been one of the major hidden dangers to the operational safety of dams. Traditional detection methods such as manual inspection and termite baiting have limitations in terms of efficiency and accuracy. To solve the problems, paper proposes a termite nest detection method based on ground penetrating radar (GPR) and deep learning. First, the simulated GPR data are generated using gprMax software, and the real data are collected using a GPR at several dams. Subsequently, the YOLOv8 deep neural network is employed for termite nest recognition in GPR images. The experimental results show that the proposed model can achieve the mean average precision (mAP) of 0.96 and a detection speed of 53.76 frames per second (FPS). © Published under licence by IOP Publishing Ltd.

关键词： Deep neural networks

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A Semi-Supervised Root Cause Identification Method for Alarm Floods via Graph-Based Manifold Regularization 43

A Semi-Supervised Root Cause Identification Method for Alarm...

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43rd Chinese control Conference, CCC 2024

作者： Chen, Ning Hu, Wenkai Liu, Zhe Wang, Fei China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China Petrochemical Company Limited Wuhan430082 China

ISBN: (纸本)9789887581581

An alarm flood is a situation where the alarm rate is too high and exceeds the operator's management ability. The occurrence and propagation of an alarm flood cause difficulties for the operators to respond to critical alarms in time, which may make the situation further deteriorate into an industrial accident. In this paper, a semi-supervised method is proposed for root cause identification of alarm floods via graph-based manifold regularization. A vector representation method for industrial alarm event data is presented based on word embedding for alarm textual encoding. A semi-supervised method is proposed to identify root causes of alarm floods based on both labeled and unlabeled alarm flood sequences. The effectiveness of the proposed method is demonstrated by a case study with data generated by a public industrial simulation model. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Semi-supervised learning

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An Adaptive Padding Correlation Filter With Group Feature Fusion for Robust Visual Tracking

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1845-1860页

作者： Zihang Feng Liping Yan Yuanqing Xia Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems the School of AutomationBeijing Institute of TechnologyBeijing 100081China IEEE the School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China

In recent visual tracking research,correlation filter(CF)based trackers become popular because of their high speed and considerable *** methods mainly work on the extension of features and the solution of the boundary effect to learn a better correlation ***,the related studies are *** exploring the potential of trackers in these two aspects,a novel adaptive padding correlation filter(APCF)with feature group fusion is proposed for robust visual tracking in this paper based on the popular context-aware tracking *** the tracker,three feature groups are fused by use of the weighted sum of the normalized response maps,to alleviate the risk of drift caused by the extreme change of single ***,to improve the adaptive ability of padding for the filter training of different object shapes,the best padding is selected from the preset pool according to tracking precision over the whole video,where tracking precision is predicted according to the prediction model trained by use of the sequence features of the first several *** sequence features include three traditional features and eight newly constructed *** experiments demonstrate that the proposed tracker is superior to most state-of-the-art correlation filter based trackers and has a stable improvement compared to the basic trackers.

关键词： Adaptive padding context information correlation filter(CF) feature group fusion robust visual tracking

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An Informer Based Alarm Early Prediction Method over Consecutive Alarm Monitoring Periods 22

An Informer Based Alarm Early Prediction Method over Consecu...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Jiang, Wenbin Hu, Wenkai Liu, Zhe Wang, Fei School of Automation China University of Geosciences Wuhan430074 China Petrochemical Company Limited Wuhan430082 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798331527471

Alarm systems serve as the first layer of protection for modern process industries to monitor industrial processes and ensure operational safety. However, the presence of alarm floods is common in alarm systems and may distract operators from critical alarms. To provide decision supports to operators during alarm flood situations, alarm prediction becomes a potential effective solution. The difficulty of alarm prediction lies in how to achieve high prediction accuracy over long-term consecutive alarm monitoring periods, including situations with either high or low alarm rates. Consequently, this paper presents an industrial alarm prediction method for both alarm flood periods and non-alarm flood periods. Specifically, a strategy of combining fixed-length and fixed-time sliding windows is designed. Further, an alarm prediction model based on Informer is proposed for alarm prediction under different alarm rates. A case study is presented to prove the validity of the proposed alarm prediction method. © 2024 IEEE.

关键词： Alarm systems

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Distributed Solver for Discrete-Time Lyapunov Equations over Dynamic Networks with Linear Convergence Rate

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IEEE Transactions on Cybernetics 2022年第2期52卷 937-946页

作者： Jiang, Xia Zeng, Xianlin Sun, Jian Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

The problem of solving discrete-Time Lyapunov equations (DTLEs) is investigated over multiagent network systems, where each agent has access to its local information and communicates with its neighbors. To obtain a solution to DTLE, a distributed algorithm with uncoordinated constant step sizes is proposed over time-varying topologies. The convergence properties and the range of constant step sizes of the proposed algorithm are analyzed. Moreover, a linear convergence rate is proved and the convergence performances over dynamic networks are verified by numerical simulations. © 2013 IEEE.

关键词： Convex optimization

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A Pipeline Leak Detection Method Based on MGD-KLD and On-Delay Timer 42

A Pipeline Leak Detection Method Based on MGD-KLD and On-Del...

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42nd Chinese control Conference, CCC 2023

作者： He, Jiaqi Yuan, Yan Hu, Wenkai Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

Leaks in natural gas pipelines can cause very serious safety accidents, and timely detection and remedial action can greatly reduce the losses. In recent years, pipeline leak detection has received extensive studies. Most methods use pressure sensors or acoustic sensors to detect pipelines, but there are certain limitations on the usage scenarios and detection time delays. On this basis, this paper selects maglev vibration detector to detect the vibration signal of pipelines. The difficulty lies in that, sudden changes in vibration signals due to external disturbances, may lead to false alarms. Therefore, this paper proposes a pipeline leak detection method using Multivariate Gaussian Distribution based Kullback-Leibler Divergence (MGD-KLD) and on-delay timer to reduce false alarms during the detection process. In this paper, by constructing a simulated pipeline platform for leak experiments and applying the above method to process the experimental data, the false alarm rate of pipeline leak detection can be effectively reduced. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Leak detection

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Stability Analysis for Amplidyne Electrical systems with Time-Varying Delay via a Negative-Determination Quadratic Function Lemma 42

Stability Analysis for Amplidyne Electrical Systems with Tim...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Hong-Jian Wang, Hong-Zhang Fan, Yu-Long Xie, Ke-You Zhang, Chuan-Ke School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

In this paper, the stability of Amplidyne Electrical systems (AESs) with a time-varying delay is studied. Firstly, the model of AESs with a time-varying delay is established. Secondly, an augmented Lyapunov-Krasovskii functional (LKF) is constructed. Then, a less conservative delay-dependent stability criterion for AESs with a time-varying delay is obtained by utilizing the generalized reciprocally convex combination and an advanced negative-determination quadratic function lemma. Finally, the superiority and effectiveness of the proposed criterion is verified by a numerical example. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Rotating magnetic amplifiers

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An Improved Synchronization Criterion for Time-Delayed Lur'e systems via Cubic Function Negative-Determination Lemma 42

An Improved Synchronization Criterion for Time-Delayed Lur'e...

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42nd Chinese control Conference, CCC 2023

作者： Peng, Yu-Fei Fan, Yu-Long He, Yong Shangguan, Xing-Chen School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

In this paper, the master-slave synchronization issue of chaotic Lur' e systems with time-varying-delay feedback control is investigated. Firstly, the synchronization problem of chaotic system is transformed into the stability problem of chaotic synchronization error system, which is studied based on Lyapunov-Krasovskii functional (LKF) method. Secondly, a novel augmented LKF with more cross terms that related to time-varying delay is proposed. Based on the application of the relaxation integral inequality and the reciprocally convex matrix inequality, an improved synchronization criterion is derived by using the cubic function negative-determination lemma. Finally, a numerical simulation example demonstrates the effectiveness and advantages of the proposed methods. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Synchronization

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A Feature Difference Network for Defect Detection on the Surface with complex Pattern of Ceramic Tile 42

A Feature Difference Network for Defect Detection on the Sur...

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42nd Chinese control Conference, CCC 2023

作者： Xiong, Jianru An, Jianqi Wang, Xing-Ao Ou, Huimin Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo- Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

The surface defects of ceramic tile greatly affect the service life of ceramic tile. At present, many detection methods of ceramic tile surface defects are mostly used for ceramic tiles with monochrome background or simple texture. However, many tiles with complex and irregular surface patterns are used in practical applications, but many methods cannot effectively detect surface defects in such tiles. This paper presents a double input feature difference network structure to overcome the limitation. First, a double input channel is constructed to extract features from the template image and the defect image respectively. Next, a method of feature difference is performed at different depths to suppress the background interference and prevent misclassification between different defect categories. Then a parameter-free attention module is embedded in the backbone to improve the ability of feature extraction. Experimental results show that this model effectively improves the mean average accuracy of 8.3% and the recall rate of 11.7%. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Surface defects

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