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

作者： Shi, Cun Wang, Qiyang Chen, Jing Fan, Siming Wang, Xingjian Wang, Shaoping Beihang University School of Automation Science and Electrical Engineering Beijing China Beihang University Ningbo Innovation Research Institute Ningbo China Aecc Aero-Engine Control System Institute Wuxi China

ISBN: (纸本)9798350312201

With the advantages of high fault tolerance, high reliability, high dynamic response and high power-to-weight ratio, the propfan engine is one of the most promising aircraft propulsion systems. In this paper, the model and control method of controlling the thrust of the propfan engine by controlling the blade pitch angle through the dual redundant electro-hydrostatic actuator (EHA) are constructed. The variable pitch propfan engine model is constructed by physical mathematical analysis, interpolation fitting and so on. The thrust control of variable pitch engine by dual redundancy EHA is completed by two-phase current control, fuzzy control and other control methods. The reliability of the constructed model and the better response characteristics of the design control method are verified by comparing the simulation experiment with the public data set. This paper provides a reference for thrust control of variable pitch propfan engine. © 2023 IEEE.

关键词： Fuzzy control

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High-Misalignment Tolerance WPT system for UAV by Symmetric Rotating Magnetic Field

High-Misalignment Tolerance WPT System for UAV by Symmetric ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Fengshuo Yang Yu Lan Qingxuan Zhang Mingxing Xiong Jinhai Jiang Kai Song Xudong Wang Wanli Xu School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of System Engineering Academy of Military Science Beijing China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

This paper proposes an novel solenoid magnetic coupler for omnidirectional wireless charging of unmanned aerial vehicles (UAVs). The magnetic coupler features asymmetry compensation, a compact structure, high rotational and misalignment tolerance, and low magnetic leakage interference. The transmitting coils consist of three groups of solenoid coils, each comprising a large coil and a small coil connected in series. The small coil compensates for the uneven coupling caused by axial misalignment of the UAV. The excitation current phase difference of 120° in each transmitter coil group generates rotating magnetic field. The transmitting coils primarily produce horizontal magnetic fields with minimal vertical components, significantly reducing electromagnetic interference with UAV equipment. Two groups of receiving solenoid coils are conformally installed on the UAV landing gear. The topology, where each group of receiving coils is rectified and then connected in series, compensates for the uneven coupling caused by radial misalignment. Simulation results indicate that the system maintains a stable received power of 379W-477W under angular offsets of 0-360° and positional offsets of ±60mm, demonstrating excellent misalignment tolerance.

关键词： Coils Couplings Gears Simulation Inductive charging Couplers Autonomous aerial vehicles Topology Magnetic fields Solenoids

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High-Misalignment Tolerance WPT system for UAV by Symmetric Rotating Magnetic Field 26

High-Misalignment Tolerance WPT System for UAV by Symmetric ...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Yang, Fengshuo Lan, Yu Zhang, Qingxuan Xiong, Mingxing Jiang, Jinhai Song, Kai Wang, Xudong Xu, Wanli School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of System Engineering Academy of Military Science Beijing China

ISBN: (纸本)9798331521950

关键词： Drones

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LiDAR Point Cloud Map Coding Framework Based on Quadric Surface Fitting and Scene Construction 5

LiDAR Point Cloud Map Coding Framework Based on Quadric Surf...

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5th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2024

作者： Sun, Xuebin Wang, Jinxi Yang, Xiaofei School of Electrical Automation and Information Engineering Tianjin University Tianjin China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Shanghai Institute of Optics and Fine Mechanics Department of Aerospace Laser Technology and System Shanghai China

ISBN: (纸本)9798350355925

Due to rapid 3D acquisition advancements, LiDAR point clouds are prevalent in emerging applications like heritage preservation, mobile robotics, and remote sensing. Yet, the sheer data volume poses challenges for transmission and storage, especially in autonomous driving. This paper introduces an efficient coding framework for compressing large dense LiDAR point cloud maps. By recording timestamps and quaternion matrices during map construction, we reduce map compression to sequence compression. The scans are segregated into intra-frames and inter-frames. For intra-frames, a quadric surface fitting intra-prediction technique eliminates spatial redundancy. For inter-frames, by constructing the 3D scene using encoded intra-frames, the inter-frame can be simulated according to its posture and LiDAR intrinsic parameters. Coding focuses on the difference between actual and predicted point cloud data. Decoding reverses this process, reconstructing the point cloud map from the decoded sequence and quaternion matrices. KITTI dataset experiments show the point cloud map can be averagely compressed to 3.43% of its original size while maintaining centimeter-level precision. This outperforms both octree and Google Draco methods. © 2024 IEEE.

关键词： Mobile robots

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wu, Wenjing Fu, Hanjing Cui, Kaixin Liu, Zhigang Yang, Dong Shi, Dawei Beijing Institute of Technology MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China Beijing Institute of Spacecraft System Engineering Beijing100094 China

Data limitation caused by the difficulty of data acquisition, the high cost of data collection, and the changes of working conditions is a serious obstacle to the accurate lithium-ion battery SOH estimation for spacecrafts system. To achieve accurate few-shot lithium-ion battery state of health(SOH) estimation and enhance the adaptability of learning methods across varying working conditions, a domain similarity model agnostic meta-learning method (DS-MAML) is proposed. First, we design a dynamic-static feature extraction method to adequately exploit information from the limited battery data and link the obtained features by gray correlation coefficients to collect sufficient information. Then, by calculating the domain similarity between the training tasks through the maximum mean discrepancy algorithm, the training tasks are ranked to reduce the re-training time. Finally, an LSTM model is added to the meta-learning framework to capture the long-term dependency relationships between SOH and time series of the voltage, and the ranked tasks are embedded in the meta-training process to improve adaptability in different working conditions. The effectiveness of the proposed method is validated by NASA and MIT datasets, and comparative experimental results illustrate that the proposed method average error is reduced by 73%, and the running speed is increased by 20% compared with traditional MAML in few-shot scenarios. © 1965-2011 IEEE.

关键词： State of charge

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POSITIONING ACCURACY ANALYSIS FOR AN ELECTROMECHANICAL COUPLED ROBOTIC JOINT MODULE UNDER UNCERTAINTIES 14

POSITIONING ACCURACY ANALYSIS FOR AN ELECTROMECHANICAL COUPL...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety engineering, QR2MSE 2024

作者： Wu, Jun Wang, He Wang, Qiyu Qu, Hongchen Xiahou, Tangfan Chen, Cen Liu, Yu School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Center for System Reliability and Safety University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China

ISBN: (纸本)9781837242672

The robotic joint module is a typical mechatronic system that inevitably faces uncertainties from various fields. These uncertainties significantly influence its positioning accuracy. In this article, we develop a positioning accuracy analysis of a robotic joint module under such uncertainties. First, a comprehensive electromechanical coupling model is constructed by considering the information exchange rules between mechanical and electronic components. Subsequently, a positioning accuracy analysis is performed, taking into account uncertainties from different fields. A variance-based sensitivity analysis method is employed to represent the contribution of these uncertainties. Finally, simulations are carried out to evaluate the effectiveness of the proposed method. © The Institution of engineering & Technology 2024.

关键词： Sensitivity analysis

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Emotion-Aware Music Driven Movie Montage

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Journal of Computer Science & Technology 2023年第3期38卷 540-553页

作者：刘伍琴林敏轩黄海斌马重阳宋玉董未名徐常胜 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 101408China The State Key Laboratory of Multimodal Artificial Intelligence System(MAIS) Institute of AutomationChinese Academy of SciencesBeijing 100190China Kuaishou Technology Beijing 100085China School of Mechanical Engineering University of Science and Technology BeijingBeijing 100083China

In this paper, we present Emotion-Aware Music Driven Movie Montage, a novel paradigm for the challenging task of generating movie montages. Specifically, given a movie and a piece of music as the guidance, our method aims to generate a montage out of the movie that is emotionally consistent with the music. Unlike previous work such as video summarization, this task requires not only video content understanding, but also emotion analysis of both the input movie and music. To this end, we propose a two-stage framework, including a learning-based module for the prediction of emotion similarity and an optimization-based module for the selection and composition of candidate movie shots. The core of our method is to align and estimate emotional similarity between music clips and movie shots in a multi-modal latent space via contrastive learning. Subsequently, the montage generation is modeled as a joint optimization of emotion similarity and additional constraints such as scene-level story completeness and shot-level rhythm synchronization. We conduct both qualitative and quantitative evaluations to demonstrate that our method can generate emotionally consistent montages and outperforms alternative baselines.

关键词： movie montage emotion analysis audio-visual modality contrastive learning

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Construction and Completion of Operational Entity Relationship Knowledge Graph 8

Construction and Completion of Operational Entity Relationsh...

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8th International Conference on Big Data and Information Analytics, BigDIA 2022

作者： Jia, Zhen Cheng, Guangquan Huang, Kuihua Chu, Yang Jiangsu Automation Research Institute Lianyungang China College of System Engineering National University of Defense Technology Chagnsha China

ISBN: (数字)9781665487962

ISBN: (纸本)9781665487962

A construction and completion method of operational entity relationship knowledge graph (ERKG) is proposed to support tactical decision aids. The operational ERKG can be built by using a syntax indicator extraction method and an entity relationship extraction model combining syntax indicator with sentence-level context. And this ERKG can be complemented by employing a graph neural network inference model based on structured attention mechanism, and a relationship inference model combining operational entity knowledge with attention mechanism. While the entity relationship reasoning method combining the operational entity knowledge with attention mechanism is adopted to evaluate the trained relationship inference model. On the basis of structured ERKG, entity knowledge graph (EKG) and event knowledge graph (EventKG), tactical decision aid instructions can be generated by combining with the battlefield situation information. © 2022 IEEE.

关键词： Knowledge graph

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NBA-guided heuristic sampling algorithm for multi-robot task planning under temporal logic 43

NBA-guided heuristic sampling algorithm for multi-robot task...

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43rd Chinese Control Conference, CCC 2024

作者： Luo, Jiong Hua, Yongzhao Ding, Shunfu Dong, Xiwang Ren, Zhang Beihang University School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Institute of Unmanned System Beihang University Beijing100191 China

ISBN: (纸本)9789887581581

Aiming at the task planning problem of multi-robot under linear temporal logic (LTL), this paper proposes an improved sampling planning algorithm based on Nondeterministic Büchi automaton (NBA) guidance. Firstly, this paper defines a kind of LTL task planning problem, which mainly focuses on the meaningful key nodes in the task execution of each robot, and there are many sequential dependencies of task constraints. Then, an improved sampling algorithm framework is proposed, which uses a more efficient way to build a search tree and reduces the number of nodes in the tree. Furthermore, the sampling points are guided by NBA to ensure that sampling is conducive to the advancement of time-series tasks. And considering the task feasible region of each robot, the auction algorithm is introduced to optimize the local matching relationship, which greatly improves the quality of sampling points. Finally, numerical simulation is carried out to solve the LTL task planning problem. The optimality and stability of the algorithm are obviously improved, and the time consumption of this algorithm is obviously better than that of the existing advanced algorithms. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Trees (mathematics)

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An Adaptive Sliding Mode Compound Control Method of Interceptors

An Adaptive Sliding Mode Compound Control Method of Intercep...

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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Xiong, Jiafu Li, Junlong Zhang, Rui Wang, Chengcai Ran, Maopeng School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Institute of Electronic System Engineering Beijing100854 China China Academy of Electronics and Information Technology Beijing100041 China

ISBN: (纸本)9789811966125

An novelty control method utilizing adaptive sliding mode is presented for the interceptor’s autopilot system with interference in this paper. The algorithm employs the ideas of sliding mode control, radial basis neural networks and adaptive control. A fast integral sliding mode surface, defined by the angular error, is first proposed. To enhance the robustness of the closed-loop system, a sliding mode control law with partial parameters updated by neural networks is derived. Furthermore, an allocation algorithm is introduced to establish overload quickly. The strategy can avoid initial full deflection of rudder and improve the dynamic transition process between direct force and aerodynamic force in complex flight environment. Numerical simulation results bear out the availability and superiority of the designed algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sliding mode control

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