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3rd Conference on Fully Actuated system Theory and Applications, FASTA 2024

作者： Feng, Yuxin Li, Zhiqiang Liu, Yang He, Zhaoshui Li, Hongyi Guangdong University of Technology School of Automation Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China Qingdao University of Science and Technology School of Automation and Electronics Engineering Qingdao266061 China Guangdong University of Technology School of Automation Guangzhou510006 China Key Laboratory for IoT Intelligent Information Processing and System Integration of Ministry of Education Guangzhou510006 China

ISBN: (纸本)9798350373691

This article addresses an adaptive tracking control problem for uncertain high-order fully actuated (HOFA) systems with unknown parameters and disturbances. Under the framework of backstepping, the unknown parameter is estimated and the external disturbance is handled by using adaptive control and H8 technique, respectively. Moreover, the Levant differentiator is employed to reduce the computation burden. Additionally, the boundedness of signals in the closed-loop system is proven using the Lyapunov theory. Finally, the effectiveness of the proposed scheme is validated through the simulation study. © 2024 IEEE.

关键词： Backstepping

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Cooperative Differential Games Guidance Laws for Multiple Missiles Against an Active Defense Target with Multiple Defenders

Cooperative Differential Games Guidance Laws for Multiple M...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Kang, Yangrui Yu, Jianglong Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

In the scenario that multiple missiles intercept one active defense target with multiple defenders. The missiles aim to finish the tasks that intercept the target from different directions to achieve saturation and evade from the defenders at the same time and each defender aim at different missile. Different from the existing results, multiple defenders are concerned in the scenario. Firstly, the guidance problem is separated into two decoupled part which is missiles-target (MT) problem and missile-defender (MD) problem. Secondly, the linearized kinematics of MD and MT model is established. Thirdly, the guidance problem is transformed into a bilateral optimal problem and the guidance laws is obtained by solving the Hamilton function. Finally, numerical simulation is given to verify the correctness of the acquired theories. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Game theory

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Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios

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Journal of Shanghai Jiaotong University (science) 2025年 1-9页

作者： Li, Mingwang Li, Xinde Zhang, Zhentong Zhang, Zeyu Zhao, Haoming School of Software Southeast University Suzhou Jiangsu215000 China School of Automation Southeast University Nanjing210018 China School of Cyber Science and Engineering Southeast University Nanjing211102 China Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education Nanjing214135 China Nanjing Center for Applied Mathematics Nanjing211135 China Southeast University Shenzhen Research Institute Shenzhen Guangdong518063 China

As autonomous mobile robots are increasingly deployed in complex environments, traditional vision sensors and LiDAR encounter considerable limitations, particularly in detecting obstacles in blind spots or transparent objects. To address the issue of blind spots, we design a specialized haptic sensing structure and develop the haptic-aided navigation vehicle (HANV). This system integrates haptic sensors and LiDAR to deliver comprehensive perception, significantly enhancing close-range obstacle detection in areas that are typically beyond the range of conventional sensors. To tackle the challenge of transparent obstacles, which are often undetected by both vision and LiDAR sensors, we employ a fusion of haptic sensors and LiDAR. The haptic system provides physical contact feedback, ensuring reliable detection of transparent obstacles such as glass, while LiDAR offers long-range sensing capabilities. This combination enables HANV to navigate effectively in environments with transparent obstacles, overcoming the limitations of traditional sensing systems. Experiment results indicate that the proposed haptic and LiDAR integration substantially improves obstacle detection in both blind spots and environments with transparent obstacles. HANV achieves high success rates, minimal collisions, and efficient obstacle avoidance, particularly excelling in complex, confined spaces where conventional systems prove inadequate. These findings emphasize the efficacy of our approach in enhancing navigation performance in dynamic and challenging environments. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Mobile robots

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AggFollower: Aggressiveness Informed Car-Following Modeling

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Chen, Xianda Yuan, Xinyi Zhu, Meixin Zheng, Xinhu Shen, Shaojie Wang, Xuesong Wang, Yinhai Wang, Fei-Yue Guangzhou China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong SAR China School of Transportation Engineering Tongji University Shanghai China Department of Civil and Environmental Engineering University of Washington Seattle WA USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection, acceleration pattern, and fuel consumption. However, existing car-following research used limited categories of driving style through pre-defined patterns and failed to encode driving style into data-driven car-following models. To address these limitations, we propose the Aggressiveness Informed Car-Following (AICF) modeling approach, which embeds driving style as a dynamic input feature in data-driven car-following models. In detail, We design driving aggressiveness tokens using four physical quantities (jerk, acceleration, relative speed, and relative spacing) to capture the heterogeneity of driving aggressiveness. These tokens were then embedded into a physics-informed Long Short-Term Memory (LSTM) based car-following model for trajectory prediction. To evaluate the effectiveness of our approach, we conducted extensive experiments based on 12,540 car-following events extracted from the HighD dataset and 24,093 events from the Lyft dataset. Compared to models devoid of considerations for driving aggressiveness levels, AICF exhibits superior efficacy in mitigating the Mean Square Error (MSE) of spacing and collision rate. To the best of our knowledge, this is the first work to directly incorporate real-time driving aggressiveness tokens as input features into data-driven car-following models, enabling a more comprehensive understanding of aggressiveness in car-following behavior. IEEE

关键词： Long short-term memory

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Formation Optimization Method of Multiple Hypersonic Vehicles

Formation Optimization Method of Multiple Hypersonic Vehicl...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Yuqing Yu, Jianglong Dong, Xiwang Li, Qingdong Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

This paper constructed a collaborative combat effectiveness evaluation system with considering the characteristics and limitations of the vehicles. Firstly, multiple hypersonic vehicles formation problem is converted to an optimization problem based on the collaborative combat effectiveness evaluation system. Secondly, the relative distance and angles between vehicle and a certain reference point is selected as the formation parameters, which are chosen as optimization variables in the optimization algorithm. Thirdly, the efficiency function corresponding to each evaluation indicator is given under the constraints of the vehicle and the PSACO (particle swarm ant colony optimization) algorithm is used to solving this optimization problem. In particular, the scenario of detection and the scenario of penetration are designed respectively considering different combat requirements. Finally, it can be verified that multiple hypersonic vehicles can achieve cooperative optimal formation in two combat scenarios through the effectiveness evaluation system and the PSACO algorithm according to simulation examples. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hypersonic vehicles

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Weapon Target Assignment Based on Compensation Auction Algorithm

Weapon Target Assignment Based on Compensation Auction Algo...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Li, Xuheng Yu, Jianglong Dong, Xiwang Li, Qingdong Hua, Yongzhao Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

An improved auction algorithm named compensation auction algorithm (CAA) is proposed for the air-to-air confrontation problem in attack scenarios. First, in order to represent the conflict in assignment, a damage benefit function is established according to the guidance rules. Secondly, a multi-constraint dynamic model of multi-weapon attacking multi-target is created. Then, according to the traditional auction algorithm, a compensation mechanism is proposed and a compensation factor is introduced. Under the condition that the constraints are satisfied, the efficiency of algorithm convergence is accelerated. Finally, a simulation is carried out on the established scene by using CAA. The results show that the algorithm has an effective optimization in time consumption compared with the existing intelligent algorithms, which also meets the real-time requirements. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Combinatorial optimization

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Modeling and analysis of the influence of air gap structure size on the churning loss in wet-type permanent magnet synchronous motors

Modeling and analysis of the influence of air gap structure ...

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2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Cheng, Yunkai Li, Shuanglu Lin, Jionghui Liu, Zhicheng Jiang, Chaofan Zhang, Xinbin Yu, Tian Tianmushan Laboratory Hangzhou China Shanghai Aerospace Control Technology Research Institute Shanghai China Science and Technology on Aircraft Control Laboratory Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China Ningbo Institute of Technology Beihang University Ningbo China

Wet-type permanent magnet synchronous motors (WTPMSM) are extensively utilized to meet the power density requirements of electro-hydrostatic actuators (EHA), which are widely used in modern aircraft control systems. These motors are valued for their superior thermal performance and compact design. However, WTPMSM face a key challenge in the form of oil churning loss, especially within narrow air gaps. This churning loss can significantly impact the motor's performance and efficiency. In this paper, an analytical model has been established and computational fluid dynamics (CFD) has been employed to simulate the internal flow of the motor, thereby predicting the churning loss. The paper also investigates churning loss caused by the thread air gap in the wet motor, examining the effects of thread geometry, size, and motor speed on churning loss. Strategies such as optimizing thread design and adjusting operational parameters are proposed to mitigate churning losses. In summary, churning loss of WTPMSM is significantly influenced by the thickness of the air gap and the depth of the threads. These findings provide guidance for the design of electric motors. Future research should delve deeper into the specific impacts of various design parameters on churning losses and explore methods to reduce churning losses through enhanced motor design. © The Institution of engineering & Technology 2024.

关键词： Computational fluid dynamics

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Parallel Driving with Big Models and Foundation Intelligence in Cyber-hysical-ocial Spaces

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Research 2024年第2期2024卷 1-17页

作者： Xiao Wang Jun Huang Yonglin Tian Chen Sun Lie Yang Shanhe Lou Chen Lv Changyin Sun Fei-Yue Wang School of Artificial Intelligence Anhui UniversityHefeiChina Macao University of Science and Technology MacaoChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina MVSLab Department of Mechanical and Mechatronics EngineeringUniversity of Waterloo200 University Ave WestWaterlooON N2L3G1Canada School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs);on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the ?S?goals of parallel driving.

关键词： breakthrough integrate corners

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Reinforcement Learning based Fission-Fusion for Heterogeneous UAV Swarm under Dynamic Interference Environments 1

Reinforcement Learning based Fission-Fusion for Heterogeneou...

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1st Aerospace Frontiers Conference, AFC 2024

作者： Wang, Yufeng Zhang, Xiaorong Wang, Qing Zhang, Zhilan Zhang, Hang Dong, Xiwang Ding, Wenrui School of Institute of Unmanned System Beihang University Beijing100191 China School of Electronic Information Engineering Beihang University 100191 China School of Automation Science Electrical Engineering Beihang University Beijing100191 China School of Shen Yuan Honors College Beihang University Beijing100191 China

ISBN: (纸本)9781510681613

The control of unmanned aerial vehicle (UAV) swarms represents a complex field of study, chiefly due to the conflicting behaviors observed among individual UAVs and the impact of external movement disturbances on the swarm. However, the fission-fusion dynamics of UAV swarms in response to unknown dynamic disturbances have received comparatively less attention than their behavior in static flight. An unknown dynamic interference environments fission-fusion for heterogeneous UAV swarm via reinforcement (DEFHRL) learning algorithm is presented, which effectively addresses the challenge of fission-fusion control within unknown dynamic interference environments. Firstly, we develop a heterogeneous swarm self-organized fission-fusion control framework that enables multi-swarm fission-fusion maneuvers for UAV swarms. Next, we introduce a topological fission selection algorithm that facilitates control of fission selection under minimal interaction loads, effectively enabling controllable swarm sizes. Finally, we introduce a subgroup adversarial algorithm, grounded in reinforcement learning, designed to conduct dynamic adversarial engagements against unknown interference with minimal resource expenditure. Simulation experiments show that UAV swarms, when operating in dynamic heterogeneous environments, can successfully execute self-organized fission-fusion maneuvers, effectively safeguarding the primary swarm against heterogeneous interference. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Finite-Time and Fault-Tolerant Cooperative Guidance Against Maneuvering Target with Time and Angle Constraints

Finite-Time and Fault-Tolerant Cooperative Guidance Against ...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Huang, Ang Yu, Jianglong Dong, Xiwang Li, Qingdong Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

Cooperative guidance of multiple missiles against a non-cooperative target with angle constraint and time constraint is investigated. Firstly, guidance model is constructed from guidance kinematics. Secondly, an exponentially convergent state observer and an extended-state-observer (ESO) are designed respectively to estimate unknown target information. Thirdly, a finite time convergent cooperative guidance law with time constraint is designed in line-of-sight (LOS) direction, and the influence of observation error is considered. Another guidance law with angle constraint is designed in normal LOS direction and the scenario of actuator failure is considered. Finally, the simulation of four missiles cooperatively intercepting a maneuvering target is built to verify the feasibility of the proposed guidance laws. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： State estimation

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