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27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Lin, Fei Tian, Yonglin Wang, Yunzhe Zhang, Tengchao Zhang, Xinyuan Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Capital University of Economics and Business Beijing100070 China University of Chinese Academy of Sciences Department of Artificial Intelligence Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Department of Engineering Science 999078 China

ISBN: (纸本)9798331505929

In urban environments, complex transportation demands, including land, air, and maritime transport, are increasingly growing. While significant advancements have been made in land transportation and autonomous driving, research on urban air mobility (UAM) systems is still in its early stages. This paper presents an innovative urban air unmanned aerial vehicle (UAV) framework: AirVista, which is designed and built based on the Artificial systems, Computational experiments, and Parallel execution (ACP) approach, integrated with a multimodal large language model (MLLM) agent. Considering that UAM tasks often require UAVs to possess fine-grained spatial perception and reasoning capabilities, and given that existing MLLMs are somewhat lacking in exploring 3D spaces, this paper further proposes an instruction fine-tuning strategy integrated with 3D spatial knowledge, which has been validated experimentally for its effectiveness. Additionally, to enhance the understanding of the efficiency of MLLM for UAV tasks, this paper delves into prompt fine-tuning templates tailored for UAV task decomposition. Through experimental demonstrations, we showcase that the prompt-tuned MLLM exhibits efficient task decomposition and execution capabilities in handling complex UAV tasks. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Pager Explosion:Cybersecurity Insights and Afterthoughts

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2359-2362页

作者： Chuan Sheng Wanlun Ma Qing-Long Han Wei Zhou Xiaogang Zhu Sheng Wen Yang Xiang Fei-Yue Wang Swinburne University of Technology Hawthorn VIC 3122Australia IEEE the School of Computer and Mathematical Sciences the University of AdelaideAdelaideSouth Australia 5005Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

PAGER EXPLOSION:THE *** 2024 Lebanon pager explosions represent one of the most unexpected and devastating technological incidents in recent *** September 17 and 18,2024,thousands of pagers and walkie-talkies exploded simultaneously across Lebanon and parts of Syria,resulting in 42 deaths and more than 3500 *** handheld communication devices,previously regarded as secure and low-profile,were rigged with concealed explosives and remotely triggered by attackers.

关键词： injuries thoughts explosion

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A policy gradient algorithm integrating long and short-term rewards for soft continuum arm control

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Science China(Technological Sciences) 2022年第10期65卷 2409-2419页

作者： DONG Xiang ZHANG Jing CHENG Long XU WenJun SU Hang MEI Tao School of Electrical Engineering and Automation Anhui UniversityHefei 230601China State Key Laboratory for Control and Management of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Robotics Research Center Peng Cheng LaboratoryShenzhen 518055China

The soft continuum arm has extensive application in industrial production and human life due to its superior safety and flexibility. Reinforcement learning is a powerful technique for solving soft arm continuous control problems, which can learn an effective control policy with an unknown system model. However, it is often affected by the high sample complexity and requires huge amounts of data to train, which limits its effectiveness in soft arm control. An improved policy gradient method, policy gradient integrating long and short-term rewards denoted as PGLS, is proposed in this paper to overcome this issue. The shortterm rewards provide more dynamic-aware exploration directions for policy learning and improve the exploration efficiency of the algorithm. PGLS can be integrated into current policy gradient algorithms, such as deep deterministic policy gradient(DDPG). The overall control framework is realized and demonstrated in a dynamics simulation environment. Simulation results show that this approach can effectively control the soft arm to reach and track the targets. Compared with DDPG and other model-free reinforcement learning algorithms, the proposed PGLS algorithm has a great improvement in convergence speed and performance. In addition, a fluid-driven soft manipulator is designed and fabricated in this paper, which can verify the proposed PGLS algorithm in real experiments in the future.

关键词： soft arm control Cosserat rod deep reinforcement learning policy gradient algorithm high sample complexity

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Superior triethylamine-sensing properties based on SnO2 hollow nanospheres synthesized via one-step process

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Progress in Natural Science:Materials International 2024年第4期34卷 682-689页

作者： Mingyue Xu Shu Yan Zia Ur Rehman Jianhua Hou Liangyun Zhai Shengjie Zhu Chuanbao Cao Wanfeng Xie Junyu Zhong Jun Yang State Key Laboratory of Bio-fibers and Eco-textiles School of Electronics and Information College of Materials Science and Engineering College of Chemistry and Chemical Engineering Qingdao University College of Environmental Science and Engineering Yangzhou University State Key Laboratory of Chemical Safety SINOPEC Research Institute of Safety Engineering Co. Ltd. National Registration Center for Chemicals Ministry of Emergency Management Research Center of Materials Science Beijing Institute of Technology State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences

Due to serious harm of triethylamine（TEA） to environmental safety and human health, it is significant to synthesize gas-sensitive materials with high performance for TEA detection. However, it is still a challenge to achieve high-sensitivity detection of TEA at low temperature for a sensor synthesized through an economical and efficient method. In this work, hollow-structured SnO2（HS-SnO2） nanospheres have been fabricated by a facile, low-cost hydrothermal method in one step, which exhibit superior TEA-sensing properties, including not only ultrahigh response（127.75） for 100 ppm TEA, good selectivity, but also fast response and recovery time（17/28 s）, low detection threshold（1 ppm） and robust stability at a relatively low optimum operational temperature of 225°*** excellent gas-sensitizing performances are ascribed to porous hollow structures with rich oxygen vacancies that provide abundant active sites for raising O2adsorption and reaction of TEA and oxygen species. This work offers an effective and economical strategy for fabricating high-performance TEA sensors for industrial applications.

关键词： Hollow-structured SnO2 nanospheres TEA High response Gas sensors

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Highway Lane Change Decision-Making via Attention-Based Deep Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 567-569页

作者： Junjie Wang Qichao Zhang Dongbin Zhao State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China IEEE

Dear editor,Deep reinforcement learning(DRL),combining the perception capability of deep learning(DL)and the decision-making capability of reinforcement learning(RL)[1],has been widely investigated for autonomous driving decision-making *** this letter,Fund:supported in part by the National Natural Science Foundation of China(NSFC)(62173325);the Beijing Municipal Natural Science Foundation(L191002).

关键词： driving Deep has

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Tailored energy absorption for a novel auxetic honeycomb structure under large deformation

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Science China(Physics,Mechanics & Astronomy) 2024年第5期67卷 63-80页

作者： Xiuhui Hou Bin Wang Zichen Deng School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi'an 710129China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi'an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China

In comparison to conventional hexagonal honeycomb structures,auxetic metamaterials with re-entrant configurations have exhibited superior mechanical properties in terms of energy *** further enhance the energy absorption capacity of these materials,a novel re-entrant honeycomb configuration,named novel auxetic re-entrant honeycomb(NARH),is developed by incorporating“<>”-shaped cell walls into the conventional auxetic re-entrant honeycomb(ARH).Two analytical models for the plateau stress are formulated to consider the plastic deformation of NARH during quasi-static compression and the dynamic impact using the linear momentum ***-static compression tests on 3D printed NARH honeycomb specimens and finite element simulations are performed to verify the effectiveness of the theoretical *** exhibits higher plateau stresses compared with ARH during compression,which can be attributed to the presence of more plastic hinges formed in *** hinges,the embedded parts with inclined cell walls,not only improve stability by forming stable triangles during compression but also enhance the energy absorption capacity.A parametric study is conducted to analyze the effect of impact velocity,thickness,and incline angle of cell walls on *** simulations demonstrate higher sensitivity of the mechanical properties to impact velocity and cell wall *** ribs to the“<>”-shaped cell walls in NARH further reduces the initial peak force during dynamic crushing while maintaining high energy *** research provides valuable guidelines for the design of energy absorption metamaterials.

关键词： absorption walls shaped

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In-Plane Dynamic Crushing Behaviors of a Vertex-Based Hierarchical Auxetic Honeycomb

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Acta Mechanica Solida Sinica 2024年第1期37卷 53-62页

作者： Yichen Zan Xiuhui Hou Zichen Deng School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi'an 710072China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi'an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China

Auxetic metamaterials,which exhibit the negative Poisson’s ratio(NPR)effect,have found wide applications in many engineering ***,their high porosity inevitably weakens their bearing capacity and impact *** improve the energy absorption efficiency of auxetic honeycombs,a novel vertex-based hierarchical star-shaped honeycomb(VSH)is designed by replacing each vertex in the classical star-shaped honeycomb(SSH)with a newly added self-similar *** analytical model is built to investigate the Young’s modulus of VSH,which shows good agreement with experimental results and numerical *** in-plane dynamic crushing behaviors of VSH at three different crushing velocities are investigated,and empirical formulas for the densification strain and plateau stress are *** results reveal more stable deformation modes for VSH,attributed to the addition of self-similar star-shaped ***,compared with SSH under the same relative densities,VSH exhibits better specific energy absorption and higher plateau ***,VSH is verified to be a better candidate for energy absorption while maintaining the auxetic *** study is expected to provide a new design strategy for auxetic honeycombs.

关键词： Vertex-based hierarchical star-shaped honeycomb Auxetic honeycomb Energy absorption Plateau stress Negative Poisson's ratio

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Comprehensive Gear Shift Schedule Design for 2-AMT Electric Vehicles Based on Sparrow Search Algorithm 42

Comprehensive Gear Shift Schedule Design for 2-AMT Electric ...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Tianyi Ma, Liling Wang, Junzheng School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789887581543

With the aim of 2-AMT electric vehicles, a comprehensive shift schedule that considers both power and economy is proposed. First, the objective function of the comprehensive shift schedule is constructed, which is the weighted sum of vehicle acceleration time and vehicle power consumption per unit distance. Second, Sparrow Search Algorithm is used to solve the objective function and obtain the comprehensive shift schedule. Finally, AVL Cruise simulation software is used to simulate vehicle dynamics and economy under an NEDC. The results show that the comprehensive shift schedule is similar to the optimal power shift schedule in terms of dynamic performance, and the economy is optimized by 3%. The feasibility of the comprehensive shift schedule is verified. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Electric vehicles

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Parallel Learning:Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 603-631页

作者： Qinghai Miao Yisheng Lv Min Huang Xiao Wang Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Artificial Intelligence Anhui UniversityHefei 266114China Qingdao Academy of Intelligent Industries Qingdao 230031China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

The virtual-to-real paradigm,i.e.,training models on virtual data and then applying them to solve real-world problems,has attracted more and more attention from various domains by successfully alleviating the data shortage problem in machine *** summarize the advances in recent years,this survey comprehensively reviews the literature,from the viewport of parallel ***,an extended parallel learning framework is proposed to cover main domains including computer vision,natural language processing,robotics,and autonomous ***,a multi-dimensional taxonomy is designed to organize the literature in a hierarchical ***,the related virtual-toreal works are analyzed and compared according to the three principles of parallel learning known as description,prediction,and prescription,which cover the methods for constructing virtual worlds,generating labeled data,domain transferring,model training and testing,as well as optimizing the strategies to guide the task-oriented data generator for better learning *** issues remained in virtual-to-real are ***,the future research directions from the viewpoint of parallel learning are suggested.

关键词： Machine learning parallel learning parallel systems sim-to-real syn-to-real virtual-to-real

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Electric Dual Variable Pump controlled Hydraulic Motor 42

Electric Dual Variable Pump Controlled Hydraulic Motor

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42nd Chinese control Conference, CCC 2023

作者： Yang, Jianmin Wang, Junzheng Niu, Shanshuai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast response. However, due to the inherent nonlinearity of multiplication, it brings certain difficulties to the control. The electric double-variable pump[1] is a dual-input single-output system, and it is a nonlinear system[2]. It is necessary to linearize the system or use a nonlinear control method to control and solve the control problem of the system. In this paper, an intelligent control rule is proposed for the nonlinear problem of double input and single output. Through backstepping design[3], the nonlinear system is transformed into multiple linear subsystems. Then the original system is turned into two independent subsystems with single input and single output, which are controlled separately. The co-simulation platform based on AMESIM and Simulink[4] has been verified and compared with a single PID control algorithm to simulate the step response and sinusoidal tracking performance of the system. The results show that the response speed of the system has been greatly improved. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Backstepping

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