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Chinese Control and Decision Conference, CCDC

作者： Linxiu Chen Weili Guan Xudong Guo Yuan Li Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China School of Automation Beijing Institute of Technology Beijing China

Entity recognition is an essential component of knowledge representation and knowledge extraction research. To enhance military situation awareness through the construction of a knowledge graph, this paper presents a novel method, BERTATT_POSBiLSTMLSTMCRF, which is based on the traditional entity recognition model BERT_BiLSTM_CRF. The local location information and the impact of the entity's position in the sentence on the entity recognition task are both fully considered by introducing the attention mechanism. Additionally, an LSTM layer is added after the BiLSTM layer to deal with long-distance label dependencies while improving the model's ability to recognize long entities. Comparative experiments demonstrate that the improved model proposed in this paper is effective in entity recognition with Wikipedia data.

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An Approach for Upper Limb Movement Intention Recognition Using EEG and sEMG Fusion based on the MCPSA-CIIM

An Approach for Upper Limb Movement Intention Recognition Us...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Weiming Zhang Xiaodong Zhang Cheng Xu Guchuan Zhou Teng Zhang Yu Wang Shaanxi Key Laboratory of Intelligent Robot School of Mechanical Engineering Xi’an Jiaotong University Xi’an Shaanxi China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China

The upper limb motion intention recognition method based on electroencephalography (EEG) and surface electromyography (sEMG) fusion has achieved significant results in fields such as prosthetic control. However, most existing fusion methods use manual means to select features, which cannot capture temporal and spatial features at different scales, and ignore the correlation features between the two types of signals. To address these issues, this article proposes a fusion recognition method for upper limb motion intention EEG and sEMG based on Multi-scale Convolution, Polarized Self-Attention, and Cross Intelligence Integration Module. This article extracts multidimensional temporal and spatial features of EEG and sEMG through multi-scale convolution, and introduce polarized self-attention mechanism to filter the extracted multi-scale features. Simultaneously using cross enhancement strategy to extract correlation features between EEG and sEMG. Finally, the features are input into the classification network for recognition. This method was validated on the Jeong database, and the results showed that compared with CNN-LSTM and EEGNet, the recognition accuracy of this method increased by 2.63% and 3.15%, respectively.

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Warship Object Detection in Remote Sensing Images with Improved YOLOv5

Warship Object Detection in Remote Sensing Images with Impro...

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Chinese Automation Congress (CAC)

作者： Caiyuan Liu Yuan Li Linxiu Chen Weili Guan School of Automation Beijing Institute of Technology Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

Aiming at the task of detecting ships on the sea surface in remote sensing images, there are a lot of disturbances such as variable object sizes, cloud occlusion, complex image backgrounds, and different ship orientations, etc. In this paper, we propose a ship rotating object detection network based on the improved YOLOv5, which is constructed through the strategies of introducing Swin Transformer as a feature extraction network to enhance the feature extraction performance of the network, introducing a rotating detection head to realize the detection of the rotation angle, and modifying the network loss function to accelerate the convergence of the network. The network finally achieves a 71.7% map on ShipRSImageNet validation set, which is an improvement of 2.4% compared with the original network model. The network proposed in this paper solves the problem that the YOLOv5 algorithm is unable to detect rotating objects, and the network based on the self-attention mechanism is used to further enhance the ability to detect small objects. Finally, a ship object detector that can be used in real remote sensing satellite images is obtained.

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Research on general system level training simulation technology of mid-and high-end military uav

Research on general system level training simulation technol...

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Chinese intelligent systems Conference, CISC 2020

作者： Zhang, Qing Tong, Jiahui Li, Haifeng Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electromechanical Engineering Institute Beijing China

ISBN: (纸本)9789811584497

A common training simulation system is proposed for the general-purpose and efficient control training needs of the mid-and highend military UAV system. The general modeling technology and processconfigurable interface protocol modeling method are adopted to realize the rapid construction of flight simulation subsystem of various aircraft models. A scheme based on general bus monitoring and fast extraction equipment is designed to realize the fast embedded real-time control training of UAV with different physical devices. A self-correctable control and evaluation method of UAV training based on multi-sample statistics is proposed to enhance the targeted strengthening setting of training subjects for trainees, so as to improve training efficiency and training effect. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Extraction

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Leader-follower Formation Control for a Multi-missile system via Deep Reinforcement Learning

Leader-follower Formation Control for a Multi-missile System...

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Chinese Control and Decision Conference, CCDC

作者： Jianfeng Li Keyuan Yu Shenmin Song Center for Control Theory and Guidance Technology School of Astronautics Harbin Institute of Technology Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

The methods for the formation tracking control problem are mainly based on nonlinear control theories. Usually, the control effect of such methods heavily depends on an accurate control model and a lot of controller parameters need to be selected properly. To cope with these shortcomings, a novel reinforcement learning-based formation controller is proposed for a leader-follower multi-missile system. The deep deterministic policy gradient (DDPG) algorithm is implemented to generate the formation control signals. An interaction environment containing a leader and a follower is formulated, in which a model-free optimal control policy is obtained by a training process. The convergent actor-network is tested for a multi-missile system. Simulation results show that the formation control objective can be rapidly achieved in spite of the change of leader maneuvers. There is no need to change the hyperparameters of the policy for different kinds of formation scenarios, which shows great advantages over the conventional nonlinear control theory-based methods in terms of parameter selection.

关键词： Training Three-dimensional displays Target tracking Simulation Heuristic algorithms Process control Optimal control

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Credibility Evaluation of Aircraft HWIL Simulation Based on the Time-Varying Area Metric

Credibility Evaluation of Aircraft HWIL Simulation Based on ...

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High Performance and Smart Computing (HPSC), IEEE International Conference on

作者： Huapin Geng Ning Wang Jiahui Tong Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (数字)9798350389463

ISBN: (纸本)9798350389470

Credibility evaluation of aircraft HWIL simulation is usually measured by the degree of consistency between simulation test data and the measured data. A new method for evaluating the credibility of aircraft HWIL simulation is established based on the idea of time-varying area measurement and uncertainty measurement Mainly for univariate, single simulation, multivariable and multi-simulation. The DTW distance measurement method is used to obtain the weight coefficients of correlated multiple response variables, and the effectiveness of uncertainty measurement method in obtaining the credibility of aircraft HWIL simulation at a certain level of confidence is verified through typical examples.

关键词： Weight measurement Uncertainty Correlation Area measurement Measurement uncertainty Distance measurement Indexes

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Edge-guided image estimation for array Gm-APD Lidar in smoky environment using multi-scale depth images 6

Edge-guided image estimation for array Gm-APD Lidar in smoky...

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6th Optics Young Scientist Summit, OYSS 2023

作者： Zhang, Yinbo Li, Sining Sun, Jianfeng Jiang, Peng Zhang, Hailong Liu, Zhihui Zhu, Yuebing National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Henan Zhengzhou450000 China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China Sichuan Jiuzhou Electrical Group Company Limited Sichuan Mianyang621000 China

ISBN: (纸本)9781510672642

Limited statistical frame number and strong backscatter interference from smoke result in a photon-starved regime, severely limiting the depth imaging capability of array Gm-APD lidar in smoky environment. Here, we propose a depth image estimation algorithm that can significantly improve the integrity of targets in dense smoke environments when signal photons are starved. At the signal level, the algorithm improves the accuracy of extracting signal photons by constructing multi-scale superpixels. At the image level, using edge information of depth images at different scales to guide and fill the original scale depth image achieves efficient noise reduction and improves target integrity. It has been successfully demonstrated under different attenuation lengths and statistical frame numbers. Compared with other state-of-the-art methods, the proposed algorithm has maximum target recovery and structural similarity, especially for the attenuation length (AL) is 3.6 and statistical frame number is 1500 (imaging time is 75ms). This study is of great significance for the fast depth imaging of dynamic targets by array Gm-APD lidar in dense smoke environments. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical radar

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A fault isolation method using kernel canonical variate analysis-based contribution

A fault isolation method using kernel canonical variate anal...

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第35届中国过程控制会议

作者： Hongxin Wang Lingxia Mu Nan Feng Han Liu Ding Liu Department of Information and Control Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology School of Intelligence Science and Technology University of Science and Technology Beijing

Fault diagnosis and isolation is important for industrial system. In this paper, a kernel canonical variate analysis(KCVA) is proposed for fault isolation. KCVA is originally used as a data dimension reduction technique which can account for nonlinearity and correlations in the industrial dynamical process data. But there are some difficulties using KCVA in the construction of the contribution for the fault isolation. On the one hand, it is difficult to compute the contributions of individual variables because it is scarcely possible to find an inverse mapping from the feature space to the original space. On the other hand, a smearing effect is hardly avoided. To solve the problem, a KCVA-based contributions is proposed using the state subspace and the residual subspace which can isolate the faulty variables effectively. Simulations are conducted on the Tennessee Eastman process to verify the performance of the proposed method.

关键词： Kernel canonical variate analysis contribution plot fault isolation

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A Parallel Mapping and Planning Strategy for Micro Aerial Vehicle

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Guidance, Navigation and Control 2022年第2期2卷 125-145页

作者： Zhuo Wang Qun Zong Hongming Shen Bailing Tian Hanchen Lu School of Electrical and Information Engineering Tianjin UniversityTianjin 300072P.R.China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing 100083P.R.China

Autonomous fight is a fundamental problem for various saplications of miaro aerial vehicles(MAVs).Thanks to the dewvelopment of *** and Control(GNC)techndogle,the rsearch on this problem i abo becoming ***,safe fight in unknown,dut tered enviouments remains an open question,epeaially with real-time reguirement on onboard *** paper propoes a framnework including prlelly mapping and planning and implements it on Graphics Pmocessing Unit(GPU).First,a spherical coomlinate proijection is used in the ocupency grid map to avold menory *** that,in the planning phase,a method baed on latice state space sampling is applied to obtain mutiple rajectorfe ***,we design a series of aoft constraints to ensure that the MAV is in a safe known space with optimal *** solving the cost for each trajectory and comparison,the optimal trajectory can be *** efectivenes of the propeed strategy is demonstrated through simulation testa.

关键词： Motion planning lattice planner parallel processing

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A Generic Anti-Windup Design Under Linear Active Disturbance Rejection Control Scheme

A Generic Anti-Windup Design Under Linear Active Disturbance...

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Electrical, Automation and Computer Engineering (ICEACE), International Conference on

作者： Li Hui Xu Cheng Ji Hua Yin Zhide Hu Wanhai Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China The 3rd Research Academy of CASIC Beijing China

A generic anti-windup compensation strategy under Linear Active Disturbance Rejection Control scheme is proposed. The difference, between the controller output and the actuator output, after multiplied by a tunable parameter, together with controller output, is fed back to the extended state observer to compensate controller windup. While windup problem arises in control system, the controller output is expectedly produced, and the disadvantageous influence of nonlinearity on closed-loop dynamics is distinctly alleviated. The approach is employed to a near space vehicle with fin-deflection saturation. The numerical simulations show that the proposed approach has the better effectiveness in active disturbance rejection control designed situation than some previous anti-windup compensation strategy.

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