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Passivity-Based Robust control Against Quantified False Data Injection Attacks in Cyber-Physical Systems

IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1440-1450页

作者： Yue Zhao Ze Chen Chunjie Zhou Yu-Chu Tian Yuanqing Qin Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Computer Science Queensland University of TechnologyBrisbane QLD 4001Australia

Secure control against cyber attacks becomes increasingly significant in cyber-physical systems(CPSs).False data injection attacks are a class of cyber attacks that aim to compromise CPS functions by injecting false data such as sensor measurements and control *** quantified false data injection attacks,this paper establishes an effective defense framework from the energy conversion ***,we design an energy controller to dynamically adjust the system energy changes caused by unknown *** designed energy controller stabilizes the attacked CPSs and ensures the dynamic performance of the system by adjusting the amount of damping ***,with the disturbance attenuation technique,the burden of control system design is simplified because there is no need to design an attack *** addition,this secure control method is simple to implement because it avoids complicated mathematical *** effectiveness of our control method is demonstrated through an industrial CPS that controls a permanent magnet synchronous motor.

关键词： Cyber-physical systems energy controller energy conversion false data injection attacks L2 disturbance attenuation technology

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A Survey on Negative Transfer

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 305-329页

作者： Wen Zhang Lingfei Deng Lei Zhang Dongrui Wu the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China IEEE the School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China

Transfer learning(TL)utilizes data or knowledge from one or more source domains to facilitate learning in a target *** is particularly useful when the target domain has very few or no labeled data,due to annotation expense,privacy concerns,***,the effectiveness of TL is not always *** transfer(NT),i.e.,leveraging source domain data/knowledge undesirably reduces learning performance in the target domain,and has been a long-standing and challenging problem in *** approaches have been proposed in the literature to address this ***,there does not exist a systematic *** paper fills this gap,by first introducing the definition of NT and its causes,and reviewing over fifty representative approaches for overcoming NT,which fall into three categories:domain similarity estimation,safe transfer,and NT *** areas,including computer vision,bioinformatics,natural language processing,recommender systems,and robotics,that use NT mitigation strategies to facilitate positive transfers,are also ***,we give guidelines on NT task construction and baseline algorithms,benchmark existing TL and NT mitigation approaches on three NT-specific datasets,and point out challenges and future research *** ensure reproducibility,our code is publicized at https://***/chamwen/NT-Benchmark.

关键词： Domain adaptation domain similarity negative transfer positive transfer transfer learning

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Missile-Target Situation Assessment Model Based on Reinorcement Learning

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Journal of Shanghai Jiaotong university(Science) 2020年第5期25卷 561-568页

作者： ZHANG Yun LU Runyan CAI Yunze Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China

In situation assessment(SA)of missile versus target fighter,the traditional SA models generally have the characteristics of strong subjectivity and poor dynamic *** paper considers SA as an expectation of future returns and establishes a missile-target simulation battle *** actor-critic(AC)algorithm in reinforcement learning(RL)is used to train the evaluation network,and a missile-target SA model is established in simulation battle *** and comparative experiments show that the model can effectively estimate the expected effect of missile attack under the current situation,and it provides an effective basis for missile attack decision.

关键词： situation assessment(SA) battle model reinforcement learning(RL) actor-critic(AC)algorithm

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controllability of neighborhood Corona product networks

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Science China(Information Sciences) 2024年第12期67卷 327-328页

作者： Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology

controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability has been widely studied and applied to system engineering and control theory, power systems, aerospace, and quantum systems. Various classical criteria include the Gram matrix criterion, Kalman rank criterion, and PBH test.

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Transmission-Constrained Consensus of Multiagent Networks

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IEEE Transactions on control of Network Systems 2023年第3期10卷 1484-1495页

作者： Wang, Xiaotian Su, Housheng Huazhong University of Science and Technology School of Artificial Intelligence and Automation Hubei430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

This article studies the consensus problem for multiagent systems with transmission constraints. A novel model of multiagent systems is proposed where the information transmissions between agents are disturbed by irregular distortions or interferences (named transmission constraint functions), and this model is universal which can be applied in many cases, such as interval consensus and discarded consensus. In the transmission-constrained consensus problem, we obtain the necessary and sufficient condition that agents can converge to state consensus. Furthermore, a more general case is studied in which the system reaches an equilibrium. Based on some techniques of stability theory, the existence, uniqueness, and stability of the system equilibrium point can be proven, which means the system can reach an asymptotically stable equilibrium. Moreover, the state values of the equilibrium are only decided by the network structure and transmission constraint functions but not the agents' initial states. Finally, numerical simulations are presented to illustrate the proposed theorems and corollaries. © 2014 IEEE.

关键词： Multi agent systems

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Prompt-guided consistency learning for multi-label classification with incomplete labels

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Neural Networks 2025年

作者： Shouwen Wang Qian Wan Zihan Zhang Zhigang Zeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China Key Lab of Image Processing and Intelligent Control Ministry of Education Wuhan 430074 China Independent Researcher Wuhan 430074 China

Addressing insufficient supervision and improving model generalization are essential for multi-label classification with incomplete annotations, i.e. , partial and single positive labels. Recent studies incorporate pseudo-labels to provide additional supervision and enhance model generalization. However, the noise in pseudo-labels generated by the model tends to accumulate, resulting in confirmation bias during training. Self-correction methods, commonly used approaches for mitigating confirmation bias, rely on model predictions but remain susceptible to confirmation bias caused by visual confusion, including both visual ambiguity and similarity. To reduce visual confusion, we propose a prompt-guided consistency learning (PGCL) framework designed for two incomplete labeling settings. Specifically, we introduce an intra-category supervised contrastive loss, which imposes consistency constraints on reliable positive class samples in the feature space of each category, rather than across the feature space of all categories, as in traditional inter-category supervised contrastive loss. Building on this, the distinction between true positive and visual confusion samples for each category is enhanced through label-level contrasting of the same category. Additionally, we develop a class-specific semantic decoupling module that leverages CLIP’s strong vision-language alignment capability, since the proposed contrastive loss requires high-quality label-level representations as contrastive samples. Extensive experimental results on multiple datasets demonstrate that our method can effectively address the problems of two incomplete labeling settings and achieve state-of-the-art performance.

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Equivalent radiometric section coefficient of metal solid objects

Equivalent radiometric section coefficient of metal solid ob...

引用

2004 4th International Conference on Microwave and Millimeter Wave Technology, ICMMT 2004

作者： Zhang, Guangfeng Zhang, Zuyin Guo, Wei Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)0780384016

It is necessary to study the radiation characteristic of metal solid objects for millimeter wave passive guidance. On basis of discussing the grounded theory, the antenna temperature contrast formula of metal solid objects is presented Furthermore equivalent radiometric section coefficient based on scale-shrinking measuring theory is proposed in favor of engineering applications. The 8mm theoretical calculation and actual measurement are mostly below IK. So equivalent radiometric section coefficient gives a virtual way for engineering measurement of metal solid objects. © 2004 IEEE.

关键词： Millimeter waves

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A tube length measurement device based on acoustic method

A tube length measurement device based on acoustic method

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Chen, Yimin Qi, Jian Zhang, Xuming Ding, Mingyue Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

A low-cost device using acoustic method for measuring open-end tube length is developed. The proposed device is aimed to get the length of the tubes which are piled up together, and only one end of which is available in the warehouse or dumping areas. The device contains the emitting and receiving probes to echo the sound pulse and receive the reflection sound wave, and has been developed with discrete component circuits whose key part is the logical control circuit based on ARM. Experiments are performed in the open tubes with the lengths between 0.85m to 6m. The measurement error is below 0.5cm. For the tubes blocked by the cement or earth, the device can detect the location of obstruction automatically. Based on the acoustic method, experiments are also conducted in the blocked tubes based on Matlab software, and the analysis of the reflection wave is given. © 2011 IEEE.

关键词： MATLAB

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城市耦合风险——以人为本的复杂系统视角（英文）

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Engineering 2025年第1期 44-50页

作者：欧阳敏程泽楷马佳欣王红卫 Stergios Aristoteles Mitoulis School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology School of Management Huazhong University of Science and Technology School of Engineering University of Birmingham

The complexity of coupled risks, which refer to the compounded effects of interacting uncertainties across multiple interdependent objectives, is inherent to cities functioning as dynamic, interdependent systems. A disruption in one domain ripples across various urban systems, often with unforeseen consequences. Central to this complexity are people, whose behaviors, needs, and vulnerabilities shape risk evolution and response effectiveness. Realizing cities as complex systems centered on human needs and behaviors is essential to understanding the complexities of coupled urban risks. This paper adopts a complex systems perspective to examine the intricacies of coupled urban risks, emphasizing the critical role of human decisions and behavior in shaping these dynamics. We focus on two key dimensions: cascading hazards in urban environments and cascading failures across interdependent exposed systems in cities. Existing risk assessment models often fail to capture the complexity of these processes, particularly when factoring in human decision-making. To tackle these challenges, we advocate for a standardized taxonomy of cascading hazards, urban components, and their interactions. At its core is a people-centric perspective, emphasizing the bidirectional interactions between people and the systems that serve them. Building on this foundation, we argue the need for an integrated, people-centric risk assessment framework that evaluates event impacts in relation to the hierarchical needs of people and incorporates their preparedness and response capacities. By leveraging real-time data, advanced simulations, and innovative validation methods, this framework aims to enhance the accuracy of coupled urban risk modeling. To effectively manage coupled urban risks, cities can draw from proven strategies in real complex systems. However, given the escalating uncertainties and complexities associated with climate change, prioritizing people-centric strategies is crucial. This ap

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Discovering distinctive action parts for action recognition

Discovering distinctive action parts for action recognition

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作者： Chen, Feifei Sang, Nong Gao, Changxin Kuang, Xiaoqin Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781479957514

Recent methods based on mid-level visual concepts have shown promising capability in human action recognition field. Automatically discovering semantic entities such as parts for an action class remains challenging. In this paper, we focus on discovering distinctive action parts for recognition of human actions by learning and selecting a small number of discriminative part detectors directly from training videos. We initially train a large collection of candidate Exemplar-LDA detectors from clusters obtained by clustering spatiotemporal patches in whitened space. A novel Coverage-Entropy curve is proposed as a means of measuring the representative and discriminative capabilities of part detectors, and used to select a set of compact and meaningful detectors out of the vast candidates. By integrating these mined detectors into 'bag of parts' representation, our approach demonstrates state-of-the-art performance on the UCF50 dataset. © 2014 IEEE.

关键词： Semantics

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