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9th International Conference on Fluid Power and Mechatronics, FPM 2023

作者： Jiang, Chaofan Shang, Yaoxing Yu, Tian Li, Mingyang Wu, Shuai Liu, Zhicheng School of Automation Science and Electrical Engineering Beihang University Beijing China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China Ningbo Institute of Technology Beihang University Ningbo China Tianmushan Laboratory Xixi Octagon City Yuhang District Hangzhou China Science and Technology on Aircraft Control Laboratory Beihang University Beijing China Research Institute for Frontier Science Beihang University Beijing China

ISBN: (纸本)9798350304947

With the development of multi-electrochemical aircraft, the application of electro-hydrostatic actuators(EHA) in aircraft actuator system is increasing. The dynamic stiffness of the actuator has a non-negligible effect on the fluttering characteristics of the rudder surface. So it is necessary to study the dynamic stiffness of EHA. In this research, a method for calculating the dynamic stiffness of EHA is proposed. The mathematical model of EHA is established. The bulk modulus of hydraulic oil affected by gas content and pressure is added to the model. Build the simulation model in Simulink. The dynamic stiffness of EHA is simulated in frequency domain. Analyze the simulation results. The EHA dynamic stiffness decreases with the increase of hydraulic oil gas content in the whole frequency range. The trough frequency of dynamic stiffness amplitude decreases with the increase of hydraulic oil gas content. The EHA dynamic stiffness decreases with the increase of pump leakage coefficient in low frequency band. Therefore, in order to improve the dynamic stiffness of EHA, the hydraulic oil gas content and the piston pump leakage coefficient should be reduced. © 2023 IEEE.

关键词： Elastic moduli

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A DAOs-Based Publishing System for Advancing Open Access

A DAOs-Based Publishing System for Advancing Open Access

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Siji Ma Juanjuan Li Sangtian Guan Qinghua Ni Fei Lin Tengchao Zhang Jun Huang Fei-Yue Wang Faculty of Innovation Engineering Macau University of Science and Technology Macau China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

The development of the scientific publishing system has remarkably enhanced global accessibility to research findings and substantially increased the visibility and dissemination of academic publications. However, significant challenges still exist in effectively safeguarding the intellectual property rights of contributors, such as the unauthorized usage of materials, the complexity of enforcing intellectual property rights across various legal jurisdictions, and high instances of plagiarism and content misuse. Additionally, financial barriers related to open access may restrict the participation of economically disadvantaged researchers, potentially biasing scientific records towards more affluent research initiatives. To address these issues, a novel decentralized framework is formulated to ensure truly open access. This framework leverages blockchain for immutable record-keeping and clear attribution of authorship, to prevent unauthorized usage and plagiarism. Besides, it also utilizes a copyright-sharing model based on decentralized autonomous organizations and operations (DAOs), where smart contracts automatically enforce copyright and access policies to ensure fair compensation for authors and researchers. Furthermore, the copyright sharing model based on non-fungible tokens (NFT) and gradual ownership optimization (GOO) mechanism is proposed to ensure fair and accurate recognition and compensation for scholarly contributions.

关键词： Open Access Law Plagiarism Smart contracts Intellectual property Research initiatives Scientific publishing Nonfungible tokens Remuneration Optimization

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Multi-Home Energy Coordination Scheduling Based on Adaptive Dynamic Programming

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The International Journal of Intelligent control and systems 2024年第1期29卷 30-36页

作者： Kang Xiong Qinglai Wei Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China.

Implementing cooperative scheduling of multi-home microgrid energy and reducing the dependence on the main grid have become the focus of microgrid energy management *** paper proposes a new multi-agent adaptive dynamic programming(MAADP)method for the cooperative control of distributed home *** home is defined as a learning agent that needs to reasonably schedule the energy storage system to meet the respective load demand while accomplishing cooperative scheduling among the individual *** addition,an energy clearing center(ECC)is introduced to complete the energy exchange between each microgrid to protect the benefits of all *** proposed method adopts the learning strategy of“centralized learning and decentralized execution”to avoid the leakage of private *** experimental comparison with the benchmark method verifies that the method can realize the cooperative scheduling of each home and reduce the dependence on the main grid.

关键词： Multi-home scenarios adaptive dynamic programming(ADP) optimal home energy management smart grid

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Optimal guidance strategy for flexible load based on hybrid direct load control and time of use

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Global Energy Interconnection 2023年第3期6卷 297-307页

作者： Siyang Liu Yuan Gao Hejun Yang Xinghua Xie Yinghao Ma State Key Laboratory of Operation and Control of Renewable Energy&Storage Systems China Electric Power Research InstituteBeijing 100192P.R.China Anhui Province Key Laboratory of Renewable Energy Utilization and Energy Saving Hefei University of TechnologyHefei 230009P.R.China

The time-of-use(TOU)strategy can effectively improve the energy consumption mode of customers,reduce the peak-valley difference of load curve,and optimize the allocation of energy *** study presents an Optimal guidance mechanism of the flexible load based on strategies of direct load control and ***,this study proposes a period partitioning model,which is based on a moving boundary technique with constraint factors,and the Dunn Validity Index(DVI)is used as the objective to solve the period ***,a control strategy for the curtailable flexible load is investigated,and a TOU strategy is utilized for further modifying load ***,a price demand response strategy for adjusting transferable load is proposed in this ***,through the case study analysis of typical daily flexible load curve,the efficiency and correctness of the proposed method and model are validated and proved.

关键词： Flexible load Optimal demand response strategy Time of use Period partitioning Direct load control

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LF-3PM: a LiDAR-based Framework for Perception-aware Planning with Perturbation-induced Metric

arXiv

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arXiv 2024年

作者： Chai, Kaixin Xu, Long Wang, Qianhao Xu, Chao Yin, Peng Gao, Fei State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China City University of Hong Kong Hong Kong Huzhou Institute of Zhejiang University Huzhou313000 China

Just as humans can become disoriented in featureless deserts or thick fogs, not all environments are conducive to the Localization Accuracy and Stability (LAS) of autonomous robots. This paper introduces an efficient framework designed to enhance LiDAR-based LAS through strategic trajectory generation, known as Perception-aware Planning. Unlike vision-based frameworks, the LiDAR-based requires different considerations due to unique sensor attributes. Our approach focuses on two main aspects: firstly, assessing the impact of LiDAR observations on LAS. We introduce a perturbation-induced metric to provide a comprehensive and reliable evaluation of LiDAR observations. Secondly, we aim to improve motion planning efficiency. By creating a Static Observation Loss Map (SOLM) as an intermediary, we logically separate the time-intensive evaluation and motion planning phases, significantly boosting the planning process. In the experimental section, we demonstrate the effectiveness of the proposed metrics across various scenes and the feature of trajectories guided by different metrics. Ultimately, our framework is tested in a real-world scenario, enabling the robot to actively choose topologies and orientations preferable for localization. The source code is accessible at https://***/ZJU-FAST-Lab/LF-3PM. Copyright © 2024, The Authors. All rights reserved.

关键词： Optical radar

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Fabrication of helical flutes on the micro-drill surface by micro-EDM using composite disc foil electrodes

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International Journal of Advanced Manufacturing technology 2025年第5期138卷 2357-2367页

作者： Xu, Bin Liu, Weitong Lian, Manqun Lei, Jianguo Wu, Xiaoyu Fu, Lianyu Zhao, Chunyang Zhang, Canbin Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518060 China Shenzhen Jinzhou Precision Technology Corp Shenzhen518116 China State Key Laboratory of Ultra-Precision Machining Technology Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong

Micro-drills are widely used in the micro-hole machining of printed circuit boards. Helical flutes, the core feature of micro-drills, play a crucial role in chip discharge. Precision grinding technology is commonly used for machining the helical flutes in micro-drills. Grinding is a contact machining technology that generates a grinding force during the process. When the diameter of the micro-drill is minimal (Φ ≤ 100 µm), the grinding force is extremely prone to cause deformation or even fracture of the micro-drill, leading to a decreased yield. To overcome the above problem, the paper proposed an approach to fabricate a helical flute structure on the surface of a micro-drill by micro electrical discharge machining (micro-EDM) using a beryllium-copper-tin composite disc foil electrode (CDFE). Micro-EDM, a type of non-contact machining, can effectively avoid the disadvantage of grinding the helical flute of the micro-drill. Through an orthogonal experiment, the effects of the rotation velocity of the CDFE, machining voltage, and pulse duration ratio on the machining quality of the helical flutes were analysed in detail. Finally, with 4000 r/min CDFE rotation velocity, 24 V machining voltage, 1 µs pulse duration and 3 µs pulse interval, a helical flute structure with a surface roughness Ra of 0.381 µm was successfully machined on the surface of a 70 µm diameter micro-drill. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Surface roughness

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Deformation Pattern Shape Sensing for Visuotactile Endoscope

Deformation Pattern Shape Sensing for Visuotactile Endoscope

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Yu, Yanzhe Tian, Yuan Cui, Shaowei Wang, Yupeng Wang, Rui Wang, Shuo Beijing University of Science and Technology Beijing100083 China The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9798350372601

The integration of visuotactile sensor technology with endoscopy enables the provision of tactile information for minimally invasive surgeries and other operations. This paper proposes a real-time sensing framework for contact deformation pattern shape, providing a foundation for precise perception in miniaturized visuotactile sensors. Specifically, we first construct a Deformation Pattern shape Descriptor (DPSD) and then track the key points in the descriptor using optical flow to obtain contact deformation shape information. Through extensive qualitative and quantitative experiments, our proposed algorithm achieves an average perception accuracy of around 83.81% for contact pattern shapes. It demonstrates consistent perception accuracy across various contact force magnitudes, directions, and scenarios, highlighting its robustness. Additionally, compared to traditional marker-level methods, it achieves a notable 46.5% improvement in displacement field perception accuracy. This research elevates tactile perception to the dimension of contact pattern shape sensing and has the potential for application in miniaturized visual tactile sensors. © 2024 IEEE.

关键词： Endoscopy

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DEEPCON: Improving Distributed Deep Learning Model Consistency in Edge-Cloud Environments via Distillation

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Qian, Bin Qian, Jiaxu Wen, Zhenyu Wu, Di He, Shibo Chen, Jiming Ranjan, Rajiv Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China Zhejiang University of Technology Institute of Cyberspace Security College of Information Engineering Hangzhou China University of St Andrews School of Computer Science United Kingdom Newcastle University United Kingdom

In a typical distributed Deep Learning (DL) based application, models are configured differently to meet the requirements of resource constraints. For instance, a large ResNet56 model is deployed on the cloud server while a small lightweight MobileNet model is more suitable for the end-user device with fewer computation resources. However, the heterogeneity of the model architectures and configurations may bring a systemic problem -models may produce different outputs when given the same input. This inconsistency problem may cause severe system failure of prediction agreement inside the application. Current research has not studied the systemic design for efficiently detecting and reducing the inconsistency among models in distributed DL applications. With the increasing scale of distributed DL applications, the challenges of inconsistency mitigation should consider both algorithm and system design. To this end, we design and implement DEEPCON, an adaptive deployment system across the edge-cloud layer with over-the-air model updates. We implement ASRS sampling for efficiently sampling data to reveal the real data distribution as well as model prediction inconsistency. Then, we implement DMML-Par, an asynchronous parallel training algorithm for quickly updating the models and reducing inconsistency. implements over-the-air updates with a set of APIS to enable seamless inconsistency detection and reduction in such deep learning applications. Our experiment results on both vision and language tasks demonstrate that DMML could improve the model consistency up to 4%, 7%, and 13% at CIFAR10/100 and IMDB datasets without sacrificing the accuracy of individual models. We also show that the ASRS sampling can save 90% network bandwidth of data transmission and that DMML-Par is up to 60% faster compared to simple synchronous parallel training. 2015 IEEE.

关键词： Distributed cloud

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A Reinforcement Learning-Based Detection Method for False Data Injection Attack in Distributed Smart Grid

A Reinforcement Learning-Based Detection Method for False Da...

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International Conference on Informative and cybernetics for Computational Social systems (ICCSS)

作者： Kuo Zhang Zheng-Guang Wu Institute of Cyber-Systems and Control Zhejiang University Hangzhou China The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781665402460

False data injection attack(FDIA) is a traditional attack for the smart grid. There are many methods for the detection of the FDIA, but few of them can send the attack alarm successfully without an attack model. In this paper, we propose a reinforcement learning-based FDIA detection method for the distributed smart grid. The detection problem is formulated as a partially observable Markov decision process(POMDP) problem, and the observation of the POMDP can be obtained from the estimation of state and attack which come from the Kalman filter. By using the Sarsa algorithm, we can get a Q-table through online training. Finally, we use the IEEE-118 bus power system to evaluate the performance of our detector, and numerical results show the accurate response for the FDIA.

关键词： Training Learning systems Estimation Distributed databases Detectors Markov processes Smart grids

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Continuous-Time LiDAR-Inertial-Vehicle Odometry Method with Lateral Acceleration Constraint

Continuous-Time LiDAR-Inertial-Vehicle Odometry Method with ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Bin He Weichen Dai Zeyu Wan Hong Zhang Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China School of Computer Science Hangzhou Dianzi University Hangzhou China Key Laboratory of Collaborative sensing and autonomous unmanned systems of Zhejiang Province Hangzhou China

In this paper, we propose a continuous-time-based LiDAR-inertial-vehicle odometry method, which can tightly fuse the data from Light Detection And Ranging (LiDAR), inertial measurement units (IMU), and vehicle measurements. The lateral acceleration constraint is further added to trajectory estimation to make the estimated trajectory follow the motion characteristics of vehicles. In addition, since vehicle model parameters vary with different motion conditions and tyre pressure, we estimate vehicle correction factors that rectify changes in vehicle model parameters online, and also analyze the observability of these vehicle correction factors. In experiments, the proposed method is evaluated and compared with state-of-the-art methods in the public dataset. The experimental results show that the proposed method achieves more accurate results in all sequences since we add additional sensor measurements and utilize the characteristic of vehicle motion to restrict the trajectory estimation. The ablation study also proved the effectiveness of continuous-time representation, online correction factor estimation, and incorporation of lateral acceleration constraint.

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