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Real-time tracking of fast-moving object in occlusion scene

Journal of systems Engineering and Electronics 2024年第3期35卷 741-752页

作者： LI Yuran LI Yichen ZHANG Monan YU Wenbin GUAN Xinping department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of systems control and Information Processing Ministry of Education of ChinaShanghai 200240China

Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.

关键词： speed-accuracy balanced motion modeling constrained updater

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Analysis of the optimal target node to reduce seizure-like discharge in networks

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Chinese Physics B 2024年第5期33卷 712-720页

作者：闫璐瑶张红慧孙中奎 School of Mathematics and Statistics Northwestern Polytechnical UniversityXi'an 710129China MIIT Key Laboratory of Dynamics and control of Complex systems Xi'an 710129China

Network approaches have been widely accepted to guide surgical strategy and predict outcome for epilepsy *** study starts with a single oscillator to explore brain activity,using a phenomenological model capable of describing healthy and epileptic *** ictal number of seizures decreases or remains unchanged with increasing the speed of oscillator excitability and in each seizure,there is an increasing tendency for ictal duration with respect to the *** underlying reason is that the strong excitability speed is conducive to reduce transition behaviors between two attractor ***,the selection of the optimal removal node is estimated by an indicator proposed in this *** show that when the indicator is less than the threshold,removing the driving node is more possible to reduce seizures significantly,while the indicator exceeds the threshold,the epileptic node could be the removal ***,the driving node is such a potential target that stimulating it is obviously effective in suppressing seizure-like activity compared to other nodes,and the propensity of seizures can be reduced 60%with the increased stimulus *** results could provide new therapeutic ideas for epilepsy surgery and neuromodulation.

关键词： epilepsy driving node epileptic node seizure regulation

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Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

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Journal of systems Engineering and Electronics 2024年第2期35卷 361-373页

作者： CHEN Chen QUAN Wei SHAO Zhuang School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent control and Decision of Complex systems Beijing 100081China

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced ***, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

关键词： target threat assessment gated recurrent unit(GRU) self-attention(SA) fractional Fourier transform(FRFT)

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Resilient sliding mode control for 2D CPSs under denial-of-service attacks

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Science China(Information Sciences) 2024年第6期67卷 262-278页

作者： Lingling LI Rongni YANG Zhiguang FENG Ligang WU College of Intelligent systems Science and Engineering Harbin Engineering University School of control Science and Engineering Shandong University School of Astronautics Harbin Institute of Technology

This study addresses the resilient sliding mode control(SMC) problem for two-dimensional cyber-physical systems(2D CPSs) characterized by the Roesser model under denial-of-service attack(DoSA), which can interfere with signal transmission over the communication network. First, the DoS-A model is established by introducing constraints on the Do S frequency and duration. Then, based on active or silent attack situations, the considered system is described as a switched mode. Furthermore, together with Lyapunov theory, the average dwell time technique is employed to deduce sufficient criteria that assure the existence of the desired sliding mode controller. Finally, verification examples are provided to show the validity of the established SMC scheme.

关键词： two-dimensional systems cyber-physical systems denial-of-service attack resilient sliding mode control

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FADSF:A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

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Computers, Materials & Continua 2024年第8期80卷 2351-2362页

作者： Yan Sun Caiyun Liu Jun Li Yitong Liu Data Security Institute China Industrial Control Systems Cyber Emergency Response TeamBeijing100040China

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage *** data of ICV(intelligent connected vehicles)is the key to organically maximizing their ***,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are *** study proposes FADSF(Fuzzy Anonymous Data Share Frame),an automobile data sharing scheme based on *** data holder publishes the shared data information and forms the corresponding label storage on the *** data demander browses the data directory information to select and purchase data assets and verify *** data demander selects and purchases data assets and verifies them by browsing the data directory ***,this paper designs a data structure Data Discrimination Bloom Filter(DDBF),making complaints about illegal *** the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing *** this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

关键词： Blockchain connected vehicles data sharing smart contracts credible traceability

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Stability in Inverse Problem of Determining Two Parameters for the Moore-Gibson-Thompson Equation with Memory Terms

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Journal of systems Science & Complexity 2024年

作者： FU Songren CHEN Liangbiao ZHANG Ji-Feng Key Laboratory of systems and control Academy of Mathematics and Systems Science Chinese Academy ofSciences School of Automation and Electrical Engineering Zhongyuan University of Technology Key Laboratory of systems and control Academy of Mathematics and Systems Science ChineseAcademy of Sciences

In this paper, the authors consider the inverse problem for the Moore-Gibson-Thompson equation with a memory term and variable diffusivity, which introduce a sort of delay in the dynamics,producing nonlocal effects in time. The H¨older stability of simultaneously determining the spatially varying viscosity coefficient and the source term is obtained by means of the key pointwise Carleman estimate for the Moore-Gibson-Thompson equation. For the sake of generality in mathematical tools,the analysis of this paper is discussed within the framework of Riemannian geometry.

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Deep Reinforcement Learning or Lyapunov Analysis?A Preliminary Comparative Study on Event-Triggered Optimal control

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1702-1704页

作者： Jingwei Lu Lefei Li Qinglai Wei Fei-Yue Wang IEEE the department of Industrial Engineering Tsinghua UniversityBeijing 100084China The State Key Laboratory for Management and control of Complex systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter develops a novel method to implement event-triggered optimal control(ETOC) for discrete-time nonlinear systems using parallel control and deep reinforcement learning(DRL), referred to as Deep-ETOC. The developed Deep-ETOC method introduces the communication cost into the performance index through parallel control, so that the developed method enables control systems to learn ETOC policies directly without triggering conditions.

关键词： Deep letter enable

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FUSE: a federated learning and U-shape split learning-based electricity theft detection framework

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Science China(Information Sciences) 2024年第4期67卷 339-340页

作者： Xuan LI Naiyu WANG Liehuang ZHU Shuai YUAN Zhitao GUAN School of control and Computer Engineering North China Electric Power University School of Cyberspace Science and Technology Beijing Institute of Technology department of Finance Operationsand Information Systems(FOIS)Brock University

In recent years, the data-driven electricity theft detection methods integrated with edge cloud computing [1, 2] have not only demonstrated superior detection accuracy but also improved efficiency, making them viable alternatives to indoor inspections. Energy service providers(ESPs) typically manage regions by dividing them into various transformer districts(TDs). The detection of electricity theft in a particular region is performed by the associated TD,

关键词： Sensitive data

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Sampling-efficient path planning and improved actor-critic-based obstacle avoidance for autonomous robots

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Science China(Information Sciences) 2024年第5期67卷 197-214页

作者： Yefeng YANG Tao HUANG Tianqi WANG Wenyu YANG Han CHEN Boyang LI Chih-yung WEN department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Center for control Theory and Guidance Technology Harbin Institute of Technology School of Engineering The University of Newcastle Research Center for Unmanned Autonomous systems The Hong Kong Polytechnic University

Autonomous robots have garnered extensive utilization in diverse fields. Among the critical concerns for autonomous systems, path planning holds paramount importance. Notwithstanding considerable efforts in its development over the years, path planning for autonomous systems continues to grapple with challenges related to low planning efficiency and inadequate obstacle avoidance response in a timely *** study proposes a novel and systematic solution to the path planning problem within intricate office buildings. The solution consists of a global planner and a local planner. To handle the global planning aspect, an adaptive clustering-based dynamic programming rapidly exploring random tree(ACDP-RRT) algorithm is proposed. ACDP-RRT effectively identifies obstacles on the map by leveraging geometric *** obstacles are then represented as a collection of sequentially arranged convex polygons, optimizing the sampling region and significantly enhancing sampling efficiency. For local planning, a network decoupling actor-critic(ND-AC) algorithm is employed. The proposed ND-AC simplifies the local planner design process by integrating planning and control loops into a neural network(NN) trained via an end-to-end model-free deep reinforcement learning(DRL) framework. Moreover, the adoption of network decoupling(ND) techniques leads to an improved obstacle avoidance success rate when compared to conventional actor-critic(AC)-based methods. Extensive simulations and experiments are conducted to demonstrate the effectiveness and robustness of the proposed approach.

关键词： rapidly exploring random tree (RRT) adaptive clustering network decoupling actor critic (AC) path planning

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Compensated acceleration feedback based active disturbance rejection control for launch vehicles

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Chinese Journal of Aeronautics 2024年第4期37卷 464-478页

作者： Xiaoyan ZHANG Wenchao XUE Zibo LIU Ran ZHANG Huifeng LI Key Laboratory of systems and control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China School of Astronautics Beihang UniversityBeijing 100191China

In this paper, the attitude tracking and load relief control problems against wind disturbances and uncertain aerodynamics as well as the engine thrust of launch vehicles are ***, a framework of Compensated Acceleration Feedback based Active Disturbance Rejection control(CAF-ADRC) is established to achieve both desired attitude tracking and load relief performances. In particular, the total disturbance that includes the effects caused by both aerocoefficient perturbations and disturbances is estimated by constructing an Extended State Observer(ESO) to achieve attitude tracking. Furthermore, combined with the normal acceleration due to the engine thrust, the accelerometer measurement is also compensated to enhance the load relief ***, the quantitative analysis of ESO and the entire closed-loop system are studied. It can be concluded that the desired attitude tracking and load relief performances can be achieved simultaneously under the proposed approach. Besides, tuning laws of the proposed approach are systematically given, which are divided into ESO, Proportional Derivative(PD) and Compensated Acceleration Feedback(CAF) modules. Moreover, the performances under CAF-ADRC approach can be better than those under CAF based PD(CAF-PD) approach by tuning load relief ***, the approach presented is applied to a typical control problem of launch vehicles with wind disturbances and parameter uncertainties.

关键词： Launch vehicles Uncertainty analysis Active disturbance rejection control(ADRC) Load relief control Extended state observer(ESO)

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