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Mission planning for repeated multi-spacecraft non-contact debris removal

Chinese Journal of Aeronautics 2025年

作者： Hang XU Lujiang LIU Yanning GUO Youmin GONG Bin SONG Guangfu MA Department of Control Science and Engineering Harbin Institute of Technology Harbin 150001 China Shanghai Institute of Aerospace System Engineering Shanghai 201109 China Zhengzhou Research Institute Harbin Institute of Technology Zhengzhou 450000 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China

Non-contact debris removal methods are fuel-efficient in a single operation compared to contact-based strategies as spacecraft don’t need to match debris velocity. To comprehensively analyze this scheme, maneuvering schemes for maximum debris removal with minimum fuel consumption, including task assignment, sequence planning, and trajectory planning, must be formulated. The coupling between variables’ dimensions and optimization results in task assignment poses challenges, as debris removal is repetitive and uncertain, leading to a vast search space. This paper proposes a novel Greedy Randomized Adaptive Search Procedure with Large Neighborhood and Crossover Mechanisms (GRASP-LNCM) to address this problem. The hybrid dynamic iteration mechanism improves computational efficiency and enhances the optimality of results. The model innovatively considers unsuccessful single removal by using a quantitative method to assess removal percentage. In addition, to improve the efficiency of sequence and trajectory planning, a Suboptimal Search Algorithm (SSA) based on the Lambert property and accelerated Multi-Revolution Lambert Problem (MRLP) solving strategy is established. Finally, a real Iridium-33 debris removal mission is studied. The simulation demonstrates that the proposed algorithm achieves state-of-the-art performance in several typical scenarios. Compared to the contact-based scheme, the new one is simpler, saving more fuel under certain conditions.

关键词： Space debris Planning Non-contact method Optimization Greedy randomized adaptive search procedure

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Distributionally Multi-level Co-optimization Dispatch Considering Primary and Secondary Frequency Regulation

Distributionally Multi-level Co-optimization Dispatch Consid...

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2020 IEEE/IAS Industrial and Commercial Power system Asia, I and CPS Asia 2020

作者： Ji, Xingquan Zhang, Yumin Ye, Pingfeng Han, Xueshan Xu, Bo Yin, Ziyang Shandong University of Science and Technology College of Electrical Engineering and Automation Qingdao China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Energy Research Institute Co. Beijing China

ISBN: (纸本)9781728143033

Distributed energy resource (DER) including wind power, solar energy and energy storage system (ESS) are connected to the active distribution network (ADN) in various combination ways, which makes the distribution network have interaction. As a bridge connecting the transmission grid (TG) and micro grid (MG), ADN breaks the traditional operation pattern of TG+ADN+MG. Considering the physical connections and shared information among TG, ADN and MG, this paper proposes a decentralized and parallel analytical target cascading (ATC) algorithm for TG+ADN+MG multi-level co-optimization dispatch considering primary and secondary frequency regulation. To explore the synergistic ability of the TG+ADN+MG coping with uncertainties of DER, i.e., wind power, the primary and secondary frequency regulation of TG are implemented to cope with uncertainties. Furthermore, the distributional uncertainties of wind power and load are well modeled by data driven, which is proposed in our previous work [1]. An improved 6-bus system is used to test the proposed model, the numerical results illustrate the effectiveness and efficiency of the proposed method. © 2020 IEEE.

关键词： Wind power

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Low-Cost Approach for Improving Video Transmission Efficiency in WVSN

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Journal of Shanghai Jiaotong university(Science) 2020年第5期25卷 600-605页

作者： LIU Min DENG Bin TANG Ying WU Minghu WANG Juan Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System.Hubei University of Technology Wuhan 430068.China Department of Electrical and Computer Engineering.Rowan University GlassboroNJ 08028USA State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Smart Education Qingdao Academy of Intelligent IndustriesQingdao 266041ShandongChina

The wireless visual sensor network(WVSN)as a new emerged intelligent visual system,has been applied in many video monitoring ***,there is still great challenge because of the limited wireless network *** resolve the problem,we propose a real-time dynamic texture approach which can detect and reduce the temporal redundancy during many successive image ***,an adaptively learning background model is improved to discover successive similar image frames from the inputting video ***,the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and background element ***,a background discarding strategy based on visual motion coherence is proposed to determine whether each image frame is streamed or *** evaluate the trade-off performance of the proposed method,it is tested on the CDW-2014 dataset,which can accurately detect the first foreground frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes,and the misdetection rate of the undetected foreground frames is near to *** to the original stream,it can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art methods.

关键词： wireless visual sensor network(WVSN) temporal redundancy foreground background dynamic texture

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Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos

arXiv

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arXiv 2021年

作者： Wang, Guangming Zeng, Honghao Wang, Ziliang Liu, Zhe Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom

Real-time 3D human pose estimation is crucial for human-computer interaction. It is cheap and practical to estimate 3D human pose only from monocular video. However, recent bone splicing based 3D human pose estimation method brings about the problem of cumulative error. In this paper, the concept of virtual bones is proposed to solve such a challenge. The virtual bones are imaginary bones between non-adjacent joints. They do not exist in reality, but they bring new loop constraints for the estimation of 3D human joints. The proposed network in this paper predicts real bones and virtual bones, simultaneously. The final length of real bones is constrained and learned by the loop constructed by the predicted real bones and virtual bones. Besides, the motion constraints of joints in consecutive frames are considered. The consistency between the 2D projected position displacement predicted by the network and the captured real 2D displacement by the camera is proposed as a new projection consistency loss for the learning of 3D human pose. The experiments on the Human3.6M dataset demonstrate the good performance of the proposed method. Ablation studies demonstrate the effectiveness of the proposed inter-frame projection consistency constraints and intra-frame loop constraints. Copyright © 2021, The Authors. All rights reserved.

关键词： E-learning

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Unobtrusive and Non-Invasive Human Activity Recognition using Kinect Sensor

Unobtrusive and Non-Invasive Human Activity Recognition usin...

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Computing, Analytics and Networks (Indo-Taiwan ICAN), Indo – Taiwan 2nd International Conference on

作者： Shalini Nehra Jagdish Lal Raheja Control & Automation Group Cyber Physical System Area CSIR-Central Electronics Engineering Research Institute Pilani India

ISBN: (数字)9781728149998

ISBN: (纸本)9781728150000

The main objective of this paper is to present a depth imaging human activity recognition system that is basically used to monitor and detect normal activities of the person in the indoor environment. The Proposed system runs in real-time and is capable of detecting moving falls, sitting fall accurately and robustly without taking into account any false positive activities. Human activity recognition with high accuracy is a huge challenge in the research world. Fall detection is an important technology in health care and elderly person activity monitoring. The proposed method is feasibility and workability are illustrated throughout the experimental result that shows the perfect human tracking and activity detection. system works well with low lighting conditions; lighting does not affect the accuracy of detecting activities. Moreover, the proposed method is able to avoid false positive as: lying down, retrieve something from the floor.

关键词： Skeleton Floors Activity recognition Feature extraction Legged locomotion Hidden Markov models Acceleration

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Research on Fault Diagnosis Method of Distributed Power Distribution Network Based on HHT and CNN

Research on Fault Diagnosis Method of Distributed Power Dist...

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第33届中国控制与决策会议

作者： Xiaodong Sun Huanxin Guan Yan Zhao Tieyan Zhang Yuri Wang Bo Yang School of Electric Power Shenyang Institute of Engineering State School of Renewable Energy Shenyang Institute of Engineering Key Laboratory of Regional Multi-energy System Integration and Control Liaoning Province School of Automation and Electrical Engineering Shenyang Ligong University State Grid Zhangye Power Supply Company

Accurate and reliable fault diagnosis is very important for improving relay protection performance and ensuring safe and stable operation of power *** paper presents a fault diagnosis method for distributed power distribution network based on convolutional neural *** fault occurs in the distribution network,FTU acquisition unit is used to sample the fault current and voltage signals of the distribution ***-Huang transform is applied to the fault signal,and a two-dimensional time-frequency energy matrix is *** the time-frequency energy matrix is input into the convolutional neural network to realize the fault type identification of transmission lines in the distribution network with distributed power *** simulation results show that the model in this paper improves the speed of fault diagnosis,makes the model more robust,and can determine and judge fault types more accurately and quickly.

关键词： Power Distribution system with Distributed Power Hilbert-Huang Transform Convolutional Neural Network Fault Classification

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Anomaly Detection of Marine Diesel Engine Valve system based on Mahalanobis Distance

Anomaly Detection of Marine Diesel Engine Valve System based...

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2020 Global Reliability and Prognostics and Health Management, PHM-Shanghai 2020

作者： Sun, Yue Xu, Aidong Wang, Kai Jia, Shuli Guo, Haifeng Han, Xiaojia Laboratory of Industrial Control Network and System State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Shenyang China Automation Engineering Department Shanghai Marine Diesel Engine Research Institute Shanghai China

ISBN: (纸本)9781728159454

Diesel engine is an important energy equipment. The valve system is the core component of diesel engine with high failure rate. It is of great significance to study the abnormal detection method of the diesel engine valve system and realize the failure warning before the failure occurs for avoiding the unexpected shutdown of the diesel engine. In this paper, an anomaly detection method of marine diesel engine valve system based on Mahalanobis distance (MD) is proposed. The failure mode of diesel engine system is analyzed. Three thermal parameters are selected as monitoring parameters for the failure mode of roller fragmentation. Fault features are extracted by MD method and the failure threshold is determined by Box-Cox transformation. Finally, the effectiveness of the proposed method is verified by the durability test of diesel engine. © 2020 IEEE.

关键词： Diesel engines

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Multi-block SSD based on small object detection for UAV railway scene surveillance

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Chinese Journal of Aeronautics 2020年第6期33卷 1747-1755页

作者： Yundong LI Han DONG Hongguang LI Xueyan ZHANG Baochang ZHANG Zhifeng XIAO North China University of Technology Beijing 100144China Key Laboratory of Large Structure Health Monitoring and Control Shijiazhuang 050043China Unmanned System Research Institute Beihang UniversityBeijing 100083China Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China State Key Laboratory of Information Engineering in Surveying Wuhan UniversityWuhan 430079China

A method of multi-block Single Shot Multi Box Detector(SSD)based on small object detection is proposed to the railway scene of unmanned aerial vehicle *** address the limitation of small object detection,a multi-block SSD mechanism,which consists of three steps,is ***,the original input images are segmented into several overlapped ***,each patch is separately fed into an SSD to detect the ***,the patches are merged together through two *** the first stage,the truncated object of the sub-layer detection result is *** the second stage,a sub-layer suppression and filtering algorithm applying the concept of non-maximum suppression is utilized to remove the overlapped boxes of *** boxes that are not detected in the main-layer are *** addition,no sufficient labeled training samples of railway circumstance are available,thereby hindering the deployment of SSD.A two-stage training strategy leveraging to transfer learning is adopted to solve this *** deep learning model is preliminarily trained using labeled data of numerous auxiliaries,and then it is refined using only a few samples of railway scene.A railway spot in China,which is easily damaged by landslides,is investigated as a case *** results show that the proposed multi-block SSD method produces an overall accuracy of 96.6%and obtains an improvement of up to 9.2%compared with the traditional SSD.

关键词： Deep learning Multi-block Single Shot MultiBox Detector(SSD) Objection detection Railway scene Unmanned aerial vehicle remote sensing

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A Variational Bayes Moving Horizon Estimation Adaptive Filter with Guaranteed Stability

arXiv

引用

arXiv 2021年

作者： Dong, Xiangxiang Battistelli, Giorgio Chisci, Luigi Cai, Yunze Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Information Engineering University of Florence Florence50139 Italy

This paper addresses state estimation of linear systems with special attention on unknown process and measurement noise covariances, aiming to enhance estimation accuracy while preserving the stability guarantee of the Kalman filter. To this end, the full information estimation problem over a finite interval is firstly addressed. Then, a novel adaptive variational Bayesian (VB) moving horizon estimation (MHE) method is proposed, exploiting VB inference, MHE and Monte Carlo integration with importance sampling for joint estimation of the unknown process and measurement noise covariances, along with the state trajectory over a moving window of fixed length. Further, it is proved that the proposed adaptive VB MHE filter ensures mean-square boundedness of the estimation error with any number of importance samples and VB iterations, as well as for any window length. Finally, simulation results on a target tracking example demonstrate the effectiveness of the VB MHE filter with enhanced estimation accuracy and convergence properties compared to the conventional non-adaptive Kalman filter and other existing adaptive filters. Copyright © 2021, The Authors. All rights reserved.

关键词： Importance sampling

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An Improved Result on Stabilization of Switched Linear systems with Time-varying Delay ⁎

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IFAC-PapersOnLine 2021年第18期54卷 96-101页

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 U.S.A.

This paper revisits the stabilization problem of switched linear systems with time-varying delay via state dependent switching strategies. In contrast to the existing works, the commonly adopted stable convex combination assumption is relaxed in this paper. For switched systems satisfying the relaxed assumption, we design a state dependent switching strategy, under which the considered system is asymptotically stable at the origin in the presence of time-varying delay. An optimization problem is formulated to estimate the upper bound of tolerable time delay. Numerical examples are presented to show that our method is applicable to a larger class of switched systems and leads to greater delay bound.

关键词： Asymptotic stability delay bound state dependent switching switched system time-varying delay

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