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Ignition of an ionic liquid dual-mode monopropellant using a microwave plasma torch

Proceedings of the Combustion Institute 2023年第4期39卷 5063-5071页

作者： Tang, Yong Li, Shaolong Yao, Zhaopu Huang, Bangdou Li, Shuiqing Key laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Energy and Power Engineering Tsinghua University Beijing100084 China Lab of Space Propulsion Technology Beijing Institute of Control Engineering Beijing100190 China Institute of Electrical Engineering Chinese Academy of Sciences Beijing100190 China School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China

The blend of hydroxylammonium nitrate (HAN) and imidazole-based ionic liquid has shown good feasibility in chemical and electric dual-mode green space propulsion. As conventional catalyst-driven ignition faces challenges arising from long preheat delay and catalyst failure, this work designs a novel ignition actuator using a microwave plasma torch. The precise tuning of the ¼-λ resonant cavity and improvement in the quality factor (QF) of the microwave igniter make the device efficient and thus allow the propellant to be ignited at a power of approximately 100 W. In the present reduced test rig, the maximum fuel flow rate corresponds to 0.1 N chemical thrusters, and the plasma-assisted ignition is mainly attributed to thermal and kinetic effects. The temperature of the actuator and the plasma torch is investigated by infrared thermometry and spectral fitting of excited molecule nitrogen, respectively. First, the hot electrode tube helps evaporate water molecules and accelerate the liquid jet through rapid gas expansion. Then, the ionic liquid quickly decomposes to small species when the flow reaches the torch with a nitrogen vibrational temperature above 4000 K and rotational temperature above 2000 K. Meanwhile, the nonequilibrium plasma-excited species enhance the combustion of gaseous intermediates by direct impact dissociation, where the OH radical profile is visualized using the planar laser-induced fluorescence technique. In addition, the copper atoms released by plasma erosion are expected to exhibit a significant catalytic effect on ionic liquid decomposition, which is a critical step in controlling the overall reaction rate. It is also noted that such mild erosion does not affect the multi-start operations during the firing test that lasts for at least 30 min. © 2022

关键词： Ionic liquids

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Reinforcement learning-enhanced dynamic multi-objective evolutionary algorithm for cooperative shovel scheduling in open-pit mining

Reinforcement learning-enhanced dynamic multi-objective evol...

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2024 China Automation Congress, CAC 2024

作者： Zhang, Zihao Li, Changhe Yang, Shengxiang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Artificial Intelligence Anhui University of Science & Technology Hefei232001 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350368604

Aiming at the ore blending problem in the open-pit mining scenario, the optimization objective is to minimize the grade variance of the sliding window of the ore flow, and a cooperative shovel scheduling model for real-time ore blending is established. A reinforcement learning-enhanced dynamic multi- objective evolutionary algorithm is proposed, where a Q-learning operator selection mechanism is introduced to reuse the information from the previous environment for tracking the optimal solution in the dynamic environment. Experimental results show that the proposed method can effectively control the grade fluctuation of the ore flow and dynamically respond to external events, and can find a better solution in real time compared with the traditional operator selection algorithm. © 2024 IEEE.

关键词： Open pit mining

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A Power Split Strategy for a Vehicular Hybrid Energy Storage System Using Adaptive Neuro Fuzzy Inference System 8

A Power Split Strategy for a Vehicular Hybrid Energy Storage...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Li, Jiao Zhang, Lijun Yang, Longzhi Wang, Bo School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Huazhong University of Science and Technology Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan430074 China Northumbria University Faculty of Engineering and Environment Department of Computer Science and Digital Technologies Newcastle upon TyneNE1 8ST United Kingdom

ISBN: (纸本)9798350300178

This paper presents a real-time power split strategy for a battery-supercapacitor hybrid energy storage system. The objective of the proposed strategy is to alleviate battery degradation through effective supercapacitor utilization. The proposed strategy employs an adaptive neural fuzzy inference system, which is capable of learning a power split strategy from offline optimization results and distributing power in real-time. The performance of the strategy proposed and a low pass filtering technique is compared through simulations. The results demonstrate that the proposed method can effectively reduce battery capacity loss and perform well under unknown driving cycles in real time. © 2023 IEEE.

关键词： Supercapacitor

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Network for hypersonic UCAV swarms

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science China(Information sciences) 2020年第4期63卷 112-139页

作者： Shixun LUO Zhongshan ZHANG Shuai WANG Shuo ZHANG Jibo DAI Xiangyuan BU Jianping AN School of Information and Electronics Beijing Institute of Technology National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute

Unmanned combat aerial vehicles(UCAVs) that swarm with both autonomous decision-making and cooperative attacking have been regarded as revolutionary elements of modern warfare. In such a swarm,inter-group connectivity must be ensured in a network to maintain a collective consensus. In recent years,academia and industry have made many efforts to achieve common tactical data link systems and commercial drone networks. However, the existing results have difficulty meeting the needs of cooperative autonomous UCAV swarms with both hypersonic mobility and time sensitivity in severe confrontation scenarios. In this article, we conduct an in-depth investigation of the network used for the hypersonic UCAV swarms,which can be considered as a special form of mobile wireless network. Furthermore, faced with specific functional demands, we summarize the main challenges of designing this dedicated network. In addition,a comprehensive survey of potential solutions for the network design is presented. Lastly, we discuss the possible capabilities of the network given the current forefront of technology, as well as remaining challenges and open issues.

关键词： military communication machine-to-machine communications multi-UCAV networks ad hoc networks wireless mesh networks unmanned aerial vehicles cross layer design

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Step-by-Step: controlling Arbitrary Style in Text with Large Language Models 30

Step-by-Step: Controlling Arbitrary Style in Text with Large...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liu, Pusheng Wu, Lianwei Wang, Linyong Guo, Sensen Liu, Yang National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University China Research & Development Institute of Northwestern Polytechnical University Shenzhen China Chongqing Science & Technology Innovation Center of Northwestern Polytechnical University China State Key Laboratory of Integrated Service Networks Xidian University China School of Artificial Intelligence Optics and Electronics Northwestern Polytechnical University China

ISBN: (纸本)9782493814104

Recently, the autoregressive framework based on large language models (LLMs) has achieved excellent performance in controlling the generated text to adhere to the required style. These methods guide LLMs through prompt learning to generate target text in an autoregressive manner. However, this manner possesses lower controllability and suffers from the challenge of accumulating errors, where early prediction inaccuracies might influence subsequent word generation. Furthermore, existing prompt-based methods overlook specific region editing, resulting in a deficiency of localized control over input text. To overcome these challenges, we propose a novel three-stage prompt-based approach for specific region editing. To alleviate the issue of accumulating errors, we transform the text style transfer task into a text infilling task, guiding the LLMs to modify only a small portion of text within the editing region to achieve style transfer, thus reducing the number of autoregressive iterations. To achieve an effective specific editing region, we adopt both prompt-based and word frequency-based strategies for region selection, subsequently employing a discriminator to validate the efficacy of the selected region. Experiments conducted on several publicly competitive datasets for text style transfer task confirm that our proposed approach achieves state-of-the-art performance. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

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A Game Theory-Reinforcement Learning Approach to Cooperation for UAVs

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IEEE Transactions on Vehicular technology 2025年第6期74卷 9864-9869页

作者： Tang, Changbing Pan, Linchao Chen, Jie Liu, Yang Lai, Jingang The College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China The School of Mathematical Sciences Zhejiang Normal University Jinhua321004 China The Hangzhou School of Automation Zhejiang Normal University Hangzhou311231 China The College of Electronic Engineering National University of Defense Technology Hefei230037 China The School of Artificial Intelligence and Automation the Key Laboratory of Image Processing and Intelligent Control Education Ministry of China China Huazhong University of Science and Technology Wuhan430074 China

To execute a variety of collaborative tasks, the cooperation for unmanned aerial vehicles (UAVs) with complicated interactions under dynamic environments is a challenging and critical issue. This paper studies the cooperation issue for UAVs under dynamic environments through an approach of game theory-reinforcement learning (GT-RL) approach, which combines the advantages of both game theory and reinforcement learning. First, to cope with the complicated interactions of UAVs, the cluster of UAVs is modeled as a public goods game with asymmetrical environmental feedback. Then, reinforcement learning is adopted to optimize decision-making of UAVs under unknown and dynamic environments through comparing the dynamic behaviors of UAVs, where a novel dynamics system offers a more comprehensive understanding on cooperative behavior among UAVs. Finally, the simulation results show that the GT-RL approach can effectively promote cooperation among UAVs in completing the collaborative tasks. © 1967-2012 IEEE.

关键词： Adversarial machine learning

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Decoupling of nitrogen and oxygen sensors based on particle swarm optimization and fuzzy feedforward compensation

Decoupling of nitrogen and oxygen sensors based on particle ...

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第43届中国控制会议

作者： Can Sun Zhen Wang Jie Wang Yu Qiao Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

A nitrogen oxide sensor that can accurately and quickly detect the content of nitrogen oxides in exhaust gas plays a key role in the treatment of automotive exhaust gas. Due to the characteristics of gas diffusion and chamber structure, nitrogen oxide sensors are difficult to achieve high-precision and fast measurement due to strong coupling. In order to solve this problem, this paper proposes a decoupling control strategy for nitrogen oxide sensors. On the one hand, the strategy uses fuzzy feedforward compensation, and on the other hand, it uses PID control based on particle swarm optimization to achieve control. This not only eliminates the coupling between loops, but also improves the control accuracy. The analysis shows that the design of the decoupling control strategy for nitrogen oxide sensors proposed in this paper is feasible, which allows the nitrogen oxide sensors to work in a stable and reliable state.

关键词： Nitrogen-oxygen sensor Coupling Adaptive PID Fuzzy feedforward decoupling

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Domain Adaptation-based Radio Frequency Fingerprint Identification for Industrial Cyber-Physical Systems

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IEEE Network 2025年

作者： Wang, Yatong Cao, Bin Wen, Zhongyi Yan, Mu Song, Changqing Beijing Institute of Technology School of Information and Electronics Beijing100081 China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100191 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100191 China

With the widespread adoption of cloud and fog platforms, security issues facing Industrial Cyber-Physical Systems (ICPSs) are increasingly prominent. Radio Frequency Fingerprinting (RFFI) emerges as a promising physical layer security technique for user authentication, effectively enhancing ICPS security over wireless networks by exploiting inherenthardware imperfections in transmitters. However, as technologies evolve and user environments become denser and more complex, existing RFFI techniques encounter significant domain shift challenges, leading to performance degradation. Therefore, developing domain-adaptive RFFI techniques is crucial for the effectiveness of ICPSs. In this article, we first provide a comprehensive review of the RFFI framework, emphasizing its applications in ICPSs and the key processes involved. Next, we focus on the domain shift issues faced by RFFI in ICPSs and present a comprehensive survey of domain adaptation methods. To tackle these challenges, we propose a novel feature-alignment based domain adaptation (FADA) framework for RFFI, which is designed to mitigate the performance degradation caused bycross-domain shifts by aligning the feature representations of the source and target domain. Finally, we discuss the inherent challenges and future directions for developing domain adaptation based RFFI to enhance the security of ICPSs. © 2025 IEEE. All rights reserved.

关键词： Radio frequency identification (RFID)

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Structural Components Recognition Method for Malfunctioned Satellite based on Domain Randomization

Structural Components Recognition Method for Malfunctioned S...

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2021 China Automation Congress, CAC 2021

作者： Du, Hang Hu, Haidong He, Yingzi Beijing Institute of Control Engineering National Key Laboratory of Science and Technology on Space Intelligent Control Beijing China

ISBN: (纸本)9781665426473

In the process of long distance non-cooperative target recognition, due to the lack of prior information, it is necessary to identify the structural components of the non-cooperative target in order to formulate the next step of approaching and capturing tasks. Most of the existing satellite recognition algorithms are based on known targets, which have poor generalization ability and cannot cope with the complex shape characteristics of space targets. This paper proposes a satellite structural components recognition algorithm based on domain randomization. Firstly, SolidWorks software is used to build the three-dimensional model of the satellite. Then, the satellite structural components dataset is generated by randomly rendering the structural components and background of the satellite 3D model. The labeled model is trained by YOLOv4 network. Finally, a physical experiment is carried out, and the experimental results show that this method provides a feasible intelligent engineering scheme. © 2021 IEEE

关键词： Satellites

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Pose Measurement Method of Non-cooperative Targets Based on Semantic Segmentation 6

Pose Measurement Method of Non-cooperative Targets Based on ...

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6th IEEE International Conference on Intelligent Computing and Signal Processing, ICSP 2021

作者： Du, Hang Hu, Haidong Xie, Xinru He, Yingzi Beijing Institute of Control Engineering National Key Laboratory of Science and Technology on Space Intelligent Control Beijing China

ISBN: (纸本)9780738143705

In the process of short-range non-cooperative target capture, the camera can only obtain a part of satellite image due to the angle of view, and it is difficult to identify the structural components and determine the capture point. This paper proposes a non-cooperative measurement method based on semantic segmentation algorithm using ToF camera. Firstly, a registration algorithm matching RGB image with depth map is designed. An improved BiseNet network is established by means of transfer learning method, and the semantic segmentation model of satellite structure components is completed. Then, the semantic matching results are combined with the point-cloud data to fit the docking ring attitude angle and to select the appropriate capturing point. Finally, physical experiment is completed and the experiment result shows the method providing a feasible intelligent engineering scheme. © 2021 IEEE.

关键词： Semantic Segmentation

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