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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Tang, Xiangyu Yu, Jianglong Dong, Xiwang Yang, Xiangyu Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733279

This paper investigates practical distance-based formation stabilization and tracking issues for nonholonomic multi-agent systems (MASs). Firstly, the agent’s nonholonomic kinematics is represented as a left invariant system on a Lie group. Through the introduction of an auxiliary state and a virtual control guided by the transverse function method, the original system is effectively converted into a fully actuated one. Secondly, under the assumption of infinitesimal and minimal rigidity in the graph, a gradient-descent-based virtual controller is devised for the transformed MASs, facilitating practical rigid formation stabilization. Thirdly, a discontinuous distributed velocity estimator is designed for formation tracking. The nonholonomic MASs achieve the desired formation shape while effectively tracking the reference trajectory. Finally, the effectiveness of the proposed method is verified by numerical examples. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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Prediction of Hybrid Asynchronous Frequency Hopping Pattern based on Deep Learning in Wideband Spectrum

Prediction of Hybrid Asynchronous Frequency Hopping Pattern ...

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2023 China Automation Congress, CAC 2023

作者： Wang, Ya Wang, Jiaqi Yuan, Shuai Liu, Naijin Lu, Yuanming Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Unit 63893 of Pla Luoyang China

ISBN: (纸本)9798350303759

In non-cooperative scenarios, wideband frequency hopping (FH) communication reconnaissance including FH signal detection, parameter estimation, and network sorting under single-channel reception is challenging. The FH pattern contains the most information about FH signals. So it is the core of FH parameter estimation. Based on the task analysis, this paper proposes a blind prediction framework combining deep learning (DL) and clustering methods to improve the accuracy and efficiency of FH pattern estimation for mixed signals in the wideband spectrum. The unique advantage of this framework is that it requires no prior signal information and anchors but exploits the inherent time-frequency (TF) properties of asynchronous FH signals. It has a strong generalization ability and can adapt to signals of any shape. Moreover, a new comprehensive evaluation metric, normalized root mean square error including missed detection (NRMSE-MD), suitable for sequence data prediction is proposed to evaluate the level of missed detection and false detection in signal monitoring. Experimental results demonstrate the superiority of the proposed framework and the effectiveness of the proposed evaluation metric. © 2023 IEEE.

关键词： Forecasting

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Predefined-time prescribed performance guidance law design against maneuvering target under input saturation 2

Predefined-time prescribed performance guidance law design a...

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2023 2nd International Conference on Aerospace and control Engineering, ICoACE 2023

作者： Wei, Zhenyan Li, Jianfeng You, Weishuai Song, Shenmin Shi, Xiaoping Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Institute of Mechanical and Electrical Engineering Beijing100072 China School of Astronautics Harbin Institute of Technology No. 92 West Dazhi Street Nangang District Harbin150001 China

A novel SMC-based prescribed performance guidance law combined with a base generator (TBG) is proposed. A TBG-based modified Lyapunov function is first proposed, which ensures that the LOS tracking error converges into zero within a predefined time. A novel sliding manifold with adjusting convergent time property is proposed, which brings about a smaller control magnitude and predefined time convergent rate. To ensure a satisfied transit and steady performance, some converted variables are defined based on which a novel prescribed performance guidance law is constructed. The input saturation problem is properly solved by designing a novel TBG-based one-order auxiliary system. Extensive simulation results have verified the effectiveness of the proposed method. © Published under licence by IOP Publishing Ltd.

关键词： Lyapunov functions

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Low Frequency Wide Bandwidth Antenna Design Using the Concept of Lumped Elements Integration 9

Low Frequency Wide Bandwidth Antenna Design Using the Concep...

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9th IEEE Asia-Pacific Conference on Antennas and Propagation, APCAP 2020

作者： Xia, Yinfeng Wang, Yanyan Li, Yingsong Xue, Wei Ye, Qiubo Harbin Engineering University College of Information and Communication Engineering Harbin China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China Jimei University School of Information Engineering Xiamen361021 China

ISBN: (纸本)9781728198057

In this paper, we will propose a super wide bandwidth low frequency antenna with a compact size for HF, VHF and UHF applications. The developed low frequency antenna consists of coplanar guide feeding structure, sleeve-like structure with lumped elements, reactance loading in the feeding. The antenna is investigated and evaluated in the HFSS, and the simulation results shows that the proposed antenna has a very wide fractional bandwidth of 191.9% from 10 MHz to 481 MHz for supporting the HF, VHF, UHF and P-band detection system applications in various platform like aircraft, ship and vehicles. © 2020 IEEE.

关键词： Bandwidth

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Vision Inertial Fusion Based on BP Neural Network for Aircraft Autonomous Positioning

Vision Inertial Fusion Based on BP Neural Network for Aircra...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Liu, Haiqiao Guan, Xujun Luo, Shibin Wu, Xia Xu, Dequan School of Automation Central South University Changsha410083 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China School of Aeronautics and Astronautics Central South University Changsha410083 China

ISBN: (纸本)9789811581540

Long-term navigation for aircraft in global position system (GPS) denied environment is a very challenging task. In this thesis, a novel aircraft autonomous positioning method based on fusion multi-modal image matching and inertial navigation system (INS) is proposed. This method consists of three steps. First, the coordinates of ground control points were obtained by matching the real-time image with the reference image. Then, PnP algorithm is employed for calculating the position of the aircraft. Finally, aircraft gets the optimal position by using BP neural network to combine the position estimated by inertial navigation and the results of multi-modal image matching. Simulation result displays that our method can effectively improve the positioning accuracy of aircraft. The accuracy of this method proposed in this thesis is comparable with that of GPS. Therefore, the study of this data fusion method has certain effects, the positioning accuracy can be improved of the aircraft. It is a great significance for the aircraft to achieve autonomous navigation. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image matching

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Visual Explanation of Object Detectors via Saliency Maps 18

Visual Explanation of Object Detectors via Saliency Maps

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Xiao, Jin Liu, Wenrui Hu, Xiaoguang Jiang, Hao Wang, Weipeng Yahang, Li Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing China Beihang University Beijing China The Third Academy of Casic Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350312201

In recent years, rapid progress of deep learning has resulted in object detection algorithms based on deep neural networks nearly completely replacing traditional methods. This shift has led to significant improvements in both accuracy and speed of object detection. However, deep neural networks that support decision-making inobject detection are complex black boxes with hidden internal logic and operations. This lack of transparency results in deep learning models being unexplainable, which limits their practical deployment. In this paper, we analyze the current state and future trends of interpretable technology in object detection and propose an effective object detection interpretable algorithm. This algorithm aims to explain the underlying logic of AI decision-making and provide support for the high performance and credibility of object detection algorithms based on deep neural networks through quantitative evaluation indicators. © 2023 IEEE.

关键词： Object detection

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Distributed Cooperative Guidance of Multi-missile with Unreliable Communications

Distributed Cooperative Guidance of Multi-missile with Unrel...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Ye, Pengpeng Wei, Jianing Lu, Yu Li, Feifei Lin, Tao Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9789811694912

The salvo attack of multi-missile is investigated, where the communication topology is randomly switching and unsustainably connected due to the unreliable links, and the probability of the packet loss is unavailable. Based on feedback linearization, a cooperative guidance protocol is developed in a fully distributed manner, in which gains can be designed incongruently for all missiles, and only the local topology information is essential. Multiple missiles disconnect with each other once the consensus of impact time is reached, and are guided to the target under the proportional navigation guidance (PNG) law individually. Sufficient conditions are established to guarantee the consensus of impact time. A simulation experiment is delivered to validate the effectiveness of the obtained results. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feedback linearization

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Multi-Source Dynamic Time Series Data Processing Method Based on Comprehensive Weighted Fusion 12

Multi-Source Dynamic Time Series Data Processing Method Base...

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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2022

作者： Geng, Huapin Yuan, Feimeng Suo, Bin Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Electro-mechanical Engineering Institute Beijing China School of Mathematics Southwest Jiaotong University Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9781839538360

Aiming at the fusion problem of multi-source heterogeneous dynamic data sources, based on the subjective and objective comprehensive weighting idea, an efficient multi-source dynamic data fusion algorithm is proposed. First, the outlier detection method based on linear regression model is used to preprocess the multi-source dynamic time series data. Then, determine the weight of the dynamic data. The prior weight of the data source is determined by the AHP method, cyclic scoring method, etc., and the posterior weight is determined according to the similarity between the time series data. Based on the Euclidean distance, a similarity measure between different data sources and a similarity measure between different dynamic data samples are constructed respectively. The former is used for the fusion of dynamic data standard deviation expectations, and the latter is used for the fusion of mean expectations. Finally, the comprehensive weight of each dynamic time series of each data source is obtained, and the comprehensive weighted fusion method is used to obtain the expected value and standard deviation of the dynamic response. The analysis of the calculation example shows that the proposed algorithm has higher computational efficiency than the method that treats dynamic data as several discrete static data. © 2022 IEEE.

关键词： Data fusion

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Research on Depth Estimation Method of Single Aerial Image 6

Research on Depth Estimation Method of Single Aerial Image

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6th IEEE Information technology, Networking, Electronic and Automation control Conference, ITNEC 2023

作者： Gao, Wang Pu, Lin Li, Lei Deng, Fei Bie, Lingzhi Beijing Institute of Mechanical and Electrical Engineering Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Wuhan University School of Geodesy and Geomatics Wuhan China Wuhan Tianjihang Information Technology Co. Ltd Wuhan China

ISBN: (纸本)9781665460033

Aiming at the problem that the current depth estimation of single image mostly uses the ground public data set, and there is less research on aerial images, this paper uses the collected visible and infrared aerial image data sets to study the depth estimation. We used FCRN and LapDRN to extract the depth estimation results of visible aerial image and infrared aerial image under global and single object respectively, and compared the results extracted from the two types of networks by qualitative and quantitative methods. The results show that the depth estimation accuracy of visible aerial image is higher than that of infrared image, but the increase rate of infrared image accuracy index is higher than the increase rate of image depth range. The image depth estimation results extracted by LapDRN method are superior to FCRN in accuracy, structure consistency and edge clarity, which indicates that LapDRN is more effective in the estimation of aerial image depth information. © 2023 IEEE.

关键词： Antennas

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Policy iteration based Q-learning for linear nonzero-sum quadratic differential games

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science China(Information sciences) 2019年第5期62卷 195-213页

作者： Xinxing LI Zhihong PENG Li LIANG Wenzhong ZHA School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Information Science Academy China Electronics Technology Group Corporation

In this paper, a policy iteration-based Q-learning algorithm is proposed to solve infinite horizon linear nonzero-sum quadratic differential games with completely unknown dynamics. The Q-learning algorithm, which employs off-policy reinforcement learning(RL), can learn the Nash equilibrium and the corresponding value functions online, using the data sets generated by behavior policies. First, we prove equivalence between the proposed off-policy Q-learning algorithm and an offline PI algorithm by selecting specific initially admissible polices that can be learned online. Then, the convergence of the off-policy Qlearning algorithm is proved under a mild rank condition that can be easily met by injecting appropriate probing noises into behavior policies. The generated data sets can be repeatedly used during the learning process, which is computationally effective. The simulation results demonstrate the effectiveness of the proposed Q-learning algorithm.

关键词： adaptive dynamic programming ADP Q-learning reinforcement learning RL linear nonzerosum quadratic differential games policy iteration PI off-policy

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