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arXiv 2023年

作者： Yu, Huan Wang, Pengqin Wang, Jin Ji, Jialin Zheng, Zhi Tu, Jie Lu, Guodong Meng, Jun Zhu, Meixin Shen, Shaojie Gao, Fei The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China The Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Hangzhou310027 China Hong Kong The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China School of Electrical Engineering Zhejiang University Hangzhou310027 China The Hong Kong University of Science and Technology Guangzhou China

Catching high-speed targets in the flight is a complex and typical highly dynamic task. However, existing methods require manual setting of catching height or time, resulting in lacks of adaptability and flexibility and cannot deal with multiple targets. To bridge this gap, we propose a planning-with-decision scheme called Catch Planner. For sequential decision making, a lightweight policy search method based on deep reinforcement learning is proposed. It is jointly trained with the motion planning and decoupled from physics to speed up training. For motion planning, we propose a trajectory optimization method that jointly optimizes the highly coupled catching time and terminal state. The core is the flexible-terminal constraint transcription. It converts the three unique constraints of catching into differentiable metrics, including equality constraints for terminal position and time, and inequality constraints that enable reasonable terminal position offset and attitude relaxation. In addition, sparse parameterization based on MINCO class considers both dynamic feasibility and collision avoidance constraints. As a result, a generally constrained quadrotor planning problem is transformed into an unconstrained optimization that can be solved reliably and efficiently. We also propose an online iterative optimization method for predicting differentiable trajectories of targets. Catch Planner provides a new paradigm for the combination of learning and planning, where all algorithms can be run in real time onboard at 100hz. Extensive experiments are carried out in real-world and simulated scenes to verify the robustness and expansibility when facing a variety of high-speed flying targets. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

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An IoT Edge Computing System Architecture and its Application

An IoT Edge Computing System Architecture and its Applicatio...

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2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Chen, Shichao Li, Qijie Zhang, Hua Zhu, Fenghua Xiong, Gang Tang, Ying Macau University of Science and Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences China Beijing University of Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Aerospace Smart Manufacturing Technology Development Co. Ltd Platform Research and Development Department Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Engineering Research Center of Intelligent Systems and Technology Institute of Automation Cloud Computing Center Chinese Academy of Sciences Beijing China Rowan University Department of Electrical and Computer Engineering GlassboroNJ United States Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (纸本)9781728168531

As the number of devices connected to the Internet of things (IoT) surges, the amount of data explodes. Therefore it not only increases the bandwidth load of data transmission but also aggravates the computing and storage load of a cloud platform. At the same time, the traditional computing paradigm centered on cloud computing cannot meet the real-time requirements in many application scenarios. The emergence of edge computing can solve the problems of realtime data processing and network bandwidth occupation in the current IoT scene. In this paper, according to the characteristics of IoT, such as fragmented data, heterogeneous network, and limited energy consumption, the architecture of an IoT edge computing system is constructed to suit better an IoT scene. In addition, the application of edge computing key technologies such as virtualization, edge intelligence, computing offload, collaborative scheduling and micro-services in resource-constrained IoT scenarios is analyzed in detail. Finally, the functions and application of energy consumption monitoring and optimization to a central air-conditioning system are analyzed and summarized, which is a typical application of edge computing in the context of the IoT. © 2020 IEEE.

关键词： Edge computing

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Comments on the article"M.O. Katanaev, Complete separation of variables in the geodesic Hamilton–Jacobi equation in four dimensions, Physica Scripta (2023), 98, 104001"

arXiv

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arXiv 2023年

作者： Obukhov, V.V. Osetrin, K.E. Shapovalov, A.V. Institute of research and development Tomsk State Pedagogical University Kievskaya str. 60 Tomsk634061 Russia Center for Mathematical and Computer Physics Tomsk State Pedagogical University Kievskaya str. 60 Tomsk634061 Russia Department of Theoretical Physics National Research Tomsk State University Lenina pr. 36 Tomsk634050 Russia International laboratory of theoretical cosmology Tomsk State University of Control Systems and Radioelectronics Lenina pr. 40 Tomsk634050 Russia

The present note is a feedback on the article by M.O. Katanaev in Physica Scripta (2023, 98, 104001), where, in our opinion, a distorted view of the classical theory of separation of variables in the Hamilton-Jacobi equation is given. We show that the metrics given in this paper, addmiting separation of variables, are special cases of V.N. Shapovalov metrics (Siberian Mathematical Journal, 1979, 20, 790), finally obtained in the 70s of the last century. The results of the article in question, unlike the original ones, do not have scientific novelty and contain omissions and incorrect *** Codes 35Q75 © 2023, CC BY-NC-ND.

关键词： Equations of motion

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Monocular Localization in Feature-Annotated 3D Polygon Maps

Monocular Localization in Feature-Annotated 3D Polygon Maps

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European Conference on Mobile Robots (ECMR)

作者： Alexander Mock Thomas Wiemann Joachim Hertzberg Knowledge Based Systems and Autonomous Robotics Groups at the Institute of Computer Science Osnabrück University Osnabrück Germany German Research Center for Artificial Intelligence (DFKI) Niedersachsen Lab Plan-Based Robot Control Group Osnabrück Germany

Localization in six degrees of freedom is becoming increasingly relevant, especially in indoor environments where GPS is not available. To localize autonomous vehicles like UAVs in such areas, reliable methods for self-localization with low-weight sensors are required. In this paper, we present an approach to precisely localize systems with monocular cameras in polygonal 3D maps annotated with keypoints and feature descriptors computed from LiDAR data and associated reference images. Our contribution consists of offline map computation from high resolution 3D point clouds with corresponding reference images as well as online localization within these maps using low cost sensors. During localization, features extracted from the vehicle’s camera image stream are matched against the reference map. The proposed method is capable of real-time localization and suitable for precise global localization. The evaluation shows comparable results to state of the art with high re-localization accuracy.

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Fabrication of translucent graded dental crown using zirconia-yttrium multi-slurry tape casting 3D printer

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Journal of the Mechanical Behavior of Biomedical Materials 2024年 152卷 106406页

作者： Romario, Yulius Shan Bhat, Chinmai Ramezani, Maziar Pasang, Tim Chen, Zhangwei Jiang, Cho-Pei Graduate Institute of Manufacturing Technology National Taipei University of Technology 1 Sec. 3 Zhongxiao E. Rd. Taipei10608 Taiwan High-value Biomaterials Research and Commercialization Center National Taipei University of Technology 1 Sec. 3 Zhongxiao E. Rd. Taipei10608 Taiwan Department of Mechanical Engineering Auckland University of Technology Auckland1010 New Zealand Department of Engineering Design Manufacturing and Management Systems Western Michigan University KalamazooMI4900-5200 United States Additive Manufacturing Institute Shenzhen University Shenzhen518060 China Guangdong Key Laboratory of Electromagnetic Control and Intelligent Robotics College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China Department of Mechanical Engineering National Taipei University of Technology 1 Sec. 3 Zhongxiao E. Rd. Taipei10608 Taiwan

This paper aims to fabricate functionally graded dental crown using a multi-slurry tape casting additive manufacturing technology. The different luminescence of the dental crown was obtained with different composition of zirconia and yttria. Zirconia with tunable mechanical properties and translucency are obtained by adding 3, 3.5, 4, 4.5, and 5 mol% of yttrium oxide to zirconia powder. After obtaining the printable slurry with maximum solid loading, the green bodies are prepared using the in-house built high-speed multi-ceramic tape casting technology. They are later sintered with two-stage sintering method. After the successful fabrication, the mechanical properties and translucency of the specimens were evaluated with Vickers hardness, three-point bending and translucency parameter tests. Finally, an FGM tooth crown with five photocurable slurries is proposed to demonstrate the translucent gradient effect of sintered part. The solid loading of 80% zirconia and 20% resin delivered samples without any surface cracks. The shrinkage ratio analysis showed that the sintered sample dimension was reduced by 20%, 20%, and 23% along X, Y, and Z directions. The samples fabricated with 3% yttrium oxide to zirconia delivered excellent hardness (1687 HV) and flexural strength (650.6 MPa). However, the relative luminescence increased with increasing the yttrium oxide for 3–5 mol%. With the optimized process parameters, the proposed dental crown is fabricated and analyzed for their shrinkage ratio, mechanical, and translucency properties. The study proposes the potential of fabricating customized dental crown with gradient translucent appearance. © 2024

关键词： Zirconia

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A Robust Nonlinear Adaptive control for control of Nuclear Reactor

A Robust Nonlinear Adaptive Control for Control of Nuclear R...

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control Conference (ICC), 2019 Sixth Indian

作者： Peddireddy M S Reddy S. R. Shimjith A. P. Tiwari Soumitra Kar Homi Bhabha National Institute Mumbai India Reactor Control Division Bhabha Atomic Research Centre Mumbai Human Resource Development Division Reactor Bhabha Atomic Research Centre Mumbai Security Electronics and Software Systems Division Bhabha Atomic Research Centre Mumbai

ISBN: (纸本)9781665409797

This paper presents a nonlinear dynamic inversion based Model Reference Adaptive control (MRAC) for nuclear reactor power control. A point kinetics model of a Pressurized Water Reactor with parameter uncertainties in thermal feedback coefficients and bounded reactivity disturbance is considered. The parameter uncertainties and disturbances are estimated based on certainty equivalence principle. Stability and boundedness of closed loop signals is verified through Lyapunov theory. Robustness of MRAC is improved with projection based modification. Finally, the efficacy of proposed adaptive controller is verified through nonlinear simulation studies.

关键词： Water Adaptation models Uncertain systems Uncertainty Power control Stability analysis Robustness

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3d-Swim: 3d Vision Based Seam Width Measurement for Industrial Composite Fiber Layup In-Situ Inspection

SSRN

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SSRN 2022年

作者： Zhang, Yinlong Yuan, Libiao Liang, Wei Xia, Xiaofang Pang, Zhibo State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Shenyang Pharmaceutical University China School of Computer Science and Technology Xidian University Xian710071 China Department of Automation Technology ABB Corporate Research Sweden Vasteras72178 Sweden Stockholm11428 Sweden

Composite fiber layup in-situ inspection plays an important role in the advanced manufacturing. An accurate seam width measurement is an indispensable procedure during the layup inspection. However, the traditional seam measurements may fail in presence of surface curvature variance, curved edges between sheets, to name a few. This paper intentionally designs a novel 3D vision based Seam Width Measurement for Industrial Composite Fiber Layup In-situ inspection (called 3D-SWiM). It aims to address three major challenges in measuring the seam width between the composite fiber sheets, namely, seam region over-segmentation, failures on region of interests (ROI) seam detection, seam width measurement inconsistency. Firstly, the region growing with semantic refinement is designed for 3D point cloud clustering, to overcome the over-segmentation on seam regions. Afterwards, the gridding model with edge discrimination is applied to extract the 3D potential candidates in the edge areas. Eventually, we use the cubic B-spline fitting model to describe the seam region curves and the improved particle swarm optimization model to estimate the minimum and maximum distance between the seam edges. Our method has been evaluated extensively on the developed composite fiber layup platform. The experimental results prove the competitive accuracy against the state-of-the-art methods in seam width measurement. © 2022, The Authors. All rights reserved.

关键词： Inspection

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Improved Direct Power control of Doubly Fed Induction Generator without Phase-Locked Loop

Improved Direct Power Control of Doubly Fed Induction Genera...

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2020 IEEE Sustainable Power and Energy Conference, iSPEC 2020

作者： Kong, Huiwen He, Jing Liu, Yikai Cheng, Peng Ma, Jing China Institute of Energy and Transportation Integrated Development North China Electric Power University Changping Direct Beijing102206 China State Key Laboratory of Operation and Control of Renewable Energy Storage Systems China Electric Power Research Institute Haidian Direct Beijing100192 China

ISBN: (纸本)9781728191645

Direct power control is widely used in renewable power generation, due to the advantages of simple implementation and fast dynamic response. This paper proposes an improved direct power control of doubly fed induction generator (DFIG) without phase-locked loop (PLL), which is implemented in the stationary reference frame. In order to deal with the time-varying voltage matrix-related dynamics of active and reactive powers for a DFIG in the stationary reference frame, the modulated active and reactive voltage are introduced. By this means, the time-varying voltage matrix-related dynamics of DFIG active and reactive powers are changed into a constant coefficient-related equation, thereby resulting in a simpler implementation. Meanwhile, the modulated rotor voltage can be obtained from the modulated active and reactive voltages based on DFIG rotor position. Then, a linear controller can be introduced to achieve the decoupling regulation and fast tracking of active and reactive powers. Finally, the experimental results are provided to confirm the effectiveness and frequency adaptability of the proposed method. © 2020 IEEE.

关键词： Wind power

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Using Multiple Neurophysiological Features to Construct the Predictive Models of Lower Limb Motor Preparation Onset

Using Multiple Neurophysiological Features to Construct the ...

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International Automatic control Conference

作者： Lo-Fan Chang Pei-Shin Lu Li-Wei Ko Chia-Hsin Chen Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electrical and Control Engineering Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B) National Yang Ming Chiao Tung University Hsinchu Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan College of Medicine Kaohsiung Medical University Kaohsiung Taiwan R.O.C. Department of Rehabilitation Medicine Kaohsiung Medical University Chung-Ho Memorial Hospital Kaohsiung Taiwan

Motor preparation (MP) is a state of brain activity that occurs for a short period of time before an exercise is performed, and it has also been shown that this brain activity is associated with neurological rehabilitation. However, it is not easy to detect this phenomenon in the lower limbs using EEG, so this study aims to construct a prediction model using multiple combinations of feature extraction, feature selection, and classifiers, and to find the optimal combination of results. In this study, 34 healthy subjects were collected to construct and test the unilateral leg MP onset detection model. PSD, PCC, and CSP were used to extract the features and find the best model combination for each of them. PSD was found to perform best when using mRMR for feature selection and a soft-voting classifier containing multiple classifier algorithms, with MP onset accuracy of 81.14±1.11% and 81.01±1.37% for the left and right legs, respectively; PCC performs best when using LinearSVM without feature selection, with MP onset accuracies of 85.46±1.24% and 85.5±1.44% for the left and right legs, respectively; CSP performs best when using LDA with feature selection, with MP onset accuracy of 81.77±1.6% and 83.29±1.57% for the left and right legs, respectively. The accuracy of all three features was more than 80%, which means that these three neurophysiological features have their physiological significance. In addition, we also analyzed the subjects' motor preparation data by MRCP and found that MRCP tended to be more pronounced in the senior subjects when they were in motor preparing. Perhaps this can be studied in depth and used as an EEG indicator in the future to be extended to the clinic.

关键词：

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Model-Based Robot Learning control with Uncertainty Directed Exploration

Model-Based Robot Learning Control with Uncertainty Directed...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Junjie Cao Yong Liu Jian Yang Zaisheng Pan Institute of Cyber Systems and Control Zhejiang University China China Research and Development Academy of Machinery Equipment Beijing China

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

The Robot with nonlinear and stochastic dynamic challenges optimal control that relying on an analytical model. Model-free reinforcement learning algorithms have shown their potential in robot learning control without an analytical or statistical dynamic model. However, requiring numerous samples hinders its application. Model-based reinforcement learning that combines dynamic model learning with model predictive control provides promising methods to control the robot with complex dynamics. Robot exploration generates diverse data for dynamic model learning. Model predictive control exploits the approximated model to select an optimal action. There is a dilemma between exploration and exploitation. Uncertainty provides a direction for robot exploring, resulting in better exploration and exploitation trade-off. In this paper, we propose Model Predictive control with Posterior Sampling (PSMPC) to make the robot learn to control efficiently. Our PSMPC does approximate sampling from the posterior of the dynamic model and applies model predictive control to achieve uncertainty directed exploration. In order to reduce the computational complexity of the resulting controller, we also propose a PSMPC guided policy optimization algorithm. The results of simulation in the high fidelity simulator “MuJoCo” show the effectiveness of our proposed robot learning control scheme.

关键词： Uncertainty Neural networks Robot learning Predictive models Nonlinear dynamical systems Data models

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