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2024 China Automation Congress, CAC 2024

作者： Zhu, Jinjin Qin, Changtao Wu, Mengxuan Shanghai Institute of Spaceflight Control Technology Shanghai Key Laboratory of Spacecraft Intelligent Control Technology Shanghai China

ISBN: (纸本)9798350368604

With the increasing deployment of high-precision optical remote sensing and observation satellites across scientific research and commercial sectors, there is a growing demand for flexible imaging modes, strong maneuverability, agility, and high-precision, stable attitude control capabilities. Complex control algorithms hinder rapid attitude maneuvers. To address the problem of rapid attitude maneuver control for satellites with multiple observation tasks, this paper proposes an adaptive path-optimal attitude maneuver control algorithm. This method autonomously plans the attitude maneuver path according to the angular momentum and torque constraints of the actuators. I t not only meets complex pointing constraints but also features fast maneuvering speed, simple structure, clear physical meaning, and easily adjustable parameters. Mathematical simulation results show that this algorithm can effectively achieve large-angle rapid maneuvers of flexible spacecraft, suppress vibrations of flexible attachments, ensure smooth and steady maneuvering processes, and demonstrate good robustness and anti-interference capabilities. © 2024 IEEE.

关键词： Maneuverability

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Feature-aided pose estimation approach based on variational auto-encoder structure for spacecrafts

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Chinese Journal of Aeronautics 2024年第8期37卷 329-341页

作者： Yanfang LIU Rui ZHOU Desong DU Shuqing CAO Naiming QI Department of Aerospace Engineering Harbin Institute of TechnologyHarbin 150001China Suzhou Research Institute of HIT Suzhou 215104China Shanghai Institute of Spaceflight Control Technology Shanghai 201109China Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai 201109China

Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit *** from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose *** improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target *** methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)*** enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole ***,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired *** evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.

关键词： Pose estimation Variational auto-encoder Feature-aided Pose Estimation Approach On-orbit measurement tasks Simulated and experimental dataset

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Continuous Self-Leaming control under System Identification based on Hopfield Neural Network

Continuous Self-Leaming Control under System Identification ...

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2024 China Automation Congress, CAC 2024

作者： Tan, Tian-Le Zhu, He Hou, Yue-Yang Zhang, Wen-Jing Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Space Intelligent Control Technology Shanghai China

ISBN: (纸本)9798350368604

Considering the dynamic modeling of an unknown and time-varying complex dynamic system in the model-based control, this paper develops a data-driven system identification method based on the Hopfield neural network (abbreviated as HNN). The normalization and denormalization transformation are designed to preprocess the training samples, and by the sliding window to refresh the sampling continuously, an online iteration method is proposed to identify the dynamic parameters. Furthermore, a continuous self-learning control based on HNN is developed in coordination with the model-based prediction and inversion control. Simulation results on the manipulator show that the HNN could efficiently identify the dynamic model in real time. The identified model has an approximately isomorphic equivalent form to the dynamic mechanism model, which could be used for the qualitative and quantitative analysis of the control quality. Results also verify the dynamic adaptability of the HNN continuous self-learning control for the nonlinear unknown and time-varying system. © 2024 IEEE.

关键词： Hopfield neural networks

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Autonomous Navigation Algorithm for GEO satellites during Hall Thruster Trajectory control in All-time

Autonomous Navigation Algorithm for GEO satellites during Ha...

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2024 China Automation Congress, CAC 2024

作者： Liu, Xiao Gao, Sihong Liang, Jupin Xiang, Kun Guo, Zhengyong Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai Aerospace Control Technology Institute Shanghai China

ISBN: (纸本)9798350368604

This paper mainly studies the autonomous navigation and orbit propagation algorithm of the Hall electric propulsion as the thrust control device for geostationary orbit satellites during the thrust control period. Compared with low-altitude satellites, high-altitude satellites generally have relatively poor GNSS velocity measurement accuracy during thrust control, as well as small thrust generated by the Hall electric propulsion, and the tachometer on the large-inertia, large-mass satellite cannot accurately measure the thrust control acceleration, resulting in a decline in the original autonomous navigation accuracy during thrust control. This paper proposes a joint autonomous navigation algorithm for the Hall electric propulsion during thrust control using the EKF and local optimal filtering. The EKF filter suppresses the measurement white noise of the GNSS positioning data, and then the local optimal filter estimates the Hall electric propulsion acceleration and feeds it back to the EKF filter algorithm in real time to improve the navigation accuracy of the Hall electric propulsion during operation. Simulation results show that the joint autonomous navigation algorithm based on the above filtering method can accurately estimate the size of the Hall electric propulsion acceleration, and can effectively improve the autonomous navigation accuracy during continuous small thrust control. © 2024 IEEE.

关键词： Extended Kalman filters

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Optimal crater landmark selection based on optical navigation performance factors for planetary landing

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Chinese Journal of Aeronautics 2023年第3期36卷 254-270页

作者： Yi XIU Shengying ZHU Rui XU Maodeng LI School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information TechnologyBeijing 100081China Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of EducationBeijing 100081China Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control EngineeringBeijing 100091China

Planetary craters are natural navigation landmarks that widely exist and are easily *** navigation based on crater landmarks has become an important autonomous navigation method for planetary *** to the increase in observed crater landmarks and the limitation of onboard computation,the selection of good crater landmarks has gradually become a research hotspot in the field of landmark-based optical *** paper designs a fast crater landmark selection method,which not only considers the configuration observability of crater subsets but also focuses on the influence on navigation performance arising from the measurement uncertainty and the matching confidence of craters,which is different from other landmark selection *** factor of measurement uncertainty,which is anisotropic,correlated and nonidentically distributed,is quantified and integrated into selection based on crater pairing detection and localization error *** addition,the concept of the crater matching confidence factor is introduced,which reflects the possibility of 2D projection measurements corresponding to 3D *** with the configuration observability factor,the crater landmark selection indicator is ***,the effectiveness of the proposed method is verified by Monte Carlo simulations.

关键词： Crater-based optical navigation Crater landmark selection Crater matching Measurement uncertainty Planetary landing

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Digitally-Assisted Analog Self-Interference Cancellation for STAR System

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China Communications 2025年第3期22卷 36-53页

作者： Pan Wensheng Shi Chengzhe Li Tong Shen Ying Shao Shihai National Key Laboratory of Wireless Communications University of Electronic Science and Technology of ChinaChengdu 611731China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China

To enable simultaneous transmit and receive(STAR)on the same frequency in a densely deployed space with multi-interference sources,this work proposes a digitally-assisted analog selfinterference cancellation method,which can acquire reference signals through flexible wired/wireless switching *** on this method,the Minimum Mean Square Error algorithm with known channel state information is derived in detail,determining the upper limit of the cancellation performance,and the Adaptive Dithered Linear Search algorithm for real-time engineering cancellation is *** correctness of theoretical analysis is verified by the practical self-interference channel measured by a vector network ***,we have designed and implemented the corresponding multiinterference cancellation prototype with the digitallyassisted structure,capable of handling multiple interferences(up to three)and supporting a large receive bandwidth of 100 MHz as well as a wide frequency coverage from 30 MHz to 3000 *** test results demonstrate that in the presence of three interferences,when the single interference bandwidth is 0.2/2/20 MHz(corresponding to the receive bandwidth of 2/20/100 MHz),the cancellation performance can reach 46/32/22 dB or more.

关键词： analog self-interference cancellation channel measurement digitally-assisted multiinterference prototype design simultaneous transmit and receive

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Interval analysis for neural networks with application to fault detection

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Science China(Information Sciences) 2024年第11期67卷 222-237页

作者： Zhenhua WANG Youdao MA Song ZHU Thach Ngoc DINH Yi SHEN Department of Control Science and Engineering Harbin Institute of Technology National Key Laboratory of Complex System Control and Intelligent Agent Cooperation School of Mathematics China University of Mining and Technology The CEDRIC-Lab Conservatoire National des Arts et Métiers (CNAM)

This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, which can compute the bounds of the output of a feedforward neural network subject to a bounded input. By applying the proposed interval analysis method to a network trained with fault-free system data, adaptive thresholds for fault detection are computed. Finally, one can acquire fault detection results via a fault detection strategy. The proposed method can achieve tight bounds of the network output and employ simple operations, which leads to accurate fault detection results and a low computational burden.A numerical simulation and an experiment on an AC servo motor are given to illustrate the effectiveness and superiority of the proposed method.

关键词： interval analysis feedforward neural network fault detection adaptive thresholds

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Deep reinforcement learning for optimal denial-of-service attacks scheduling

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Science China(Information Sciences) 2022年第6期65卷 98-106页

作者： Fangyuan HOU Jian SUN Qiuling YANG Zhonghua PANG State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of Technology

We consider an optimal denial-of-service(DoS) attack scheduling problem of N independent linear time-invariant processes, where sensors have limited computational capability. Sensors transmit measurements to the remote estimator via a communication channel that is exposed to DoS attackers. However,due to limited energy, an attacker can only attack a subset of sensors at each time step. To maximally degrade the estimation performance, a DoS attacker needs to determine which sensors to attack at each time step. In this context, a deep reinforcement learning(DRL) algorithm, which combines Q-learning with a deep neural network, is introduced to solve the Markov decision process(MDP). The DoS attack scheduling optimization problem is formulated as an MDP that is solved by the DRL algorithm. A numerical example is provided to illustrate the efficiency of the optimal DoS attack scheduling scheme using the DRL algorithm.

关键词： optimal denial-of-service attack scheduling optimization limited energy deep reinforcement learning

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D-FUSION SLAM: A VSLAM SYSTEM OPTIMIZED BY INTEGRATING DEPTH INFORMATION AND RGBD FEATURE POINTS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2025年第1期87卷 121-138页

作者： Zheng, Qingchun Wu, Moudong Zhu, Peihao Yang, Bin Li, Shubo Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China

This paper introduces D-Fusion SLAM, an advanced VSLAM system based on ORB-SLAM2. D-Fusion SLAM integrates depth information to enhance feature selection, aiming to improve accuracy and speed in visual SLAM applications. The system mainly comprises two modules: an image grid filtering module based on grayscale information and a feature selection module integrating depth information. These modules effectively eliminate redundant and useless features, ensuring high-quality features for pose estimation. We tested D-Fusion SLAM on the TUM dataset and compared it with ORB-SLAM2. Experimental results demonstrate that D-Fusion SLAM outperforms ORB-SLAM2, significantly enhancing the system's accuracy and robustness. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Feature Selection

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Predicting circRNA-Disease Associations by Using Multi-Biomolecular Networks Based on Variational Graph Auto-Encoder with Attention Mechanism

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Chinese Journal of Electronics 2024年第6期33卷 1526-1537页

作者： Jing YANG Xiujuan LEI Yi PAN School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology

CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computational model to predict the associations between circRNAs and diseases. And there is existing more and more evidence indicates that the combination of multi-biomolecular information can improve the prediction accuracy. We propose a novel computational model for CDA prediction named MBCDA, we collect the multi-biomolecular information including circRNA, disease, miRNA and lncRNA based on 6 databases, and construct three heterogeneous network among them, then the multi-heads graph attention networks are applied to these three networks to extract the features of circRNAs and diseases from different views, the obtained features are put into variational graph auto-encoder(VGAE) network to learn the latent distributions of the nodes, a fully connected neural network is adopted to further process the output of VGAE and uses sigmoid function to obtain the predicted probabilities of circRNA-disease *** a result, MBCDA achieved the values of AUC and AUPR under 5-fold cross-validation of 0.893 and 0.887. MBCDA was applied to the analysis of the top-25 predicted associations between circRNAs and diseases, these experimental results show that our proposed MBCDA is a powerful computational model for CDA prediction.

关键词： Knowledge engineering Attention mechanisms Computational modeling Biological system modeling Predictive models Feature extraction Heterogeneous networks Topology Data mining Diseases

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