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2023 Jiangsu Annual Conference on Automation, JACA 2023

作者： Xu, Lei Mao, Linxuan Li, Shihua School of Electronic Science and Engineering Southeast University Nanjing210096 China School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781839539848

This paper presents an enhanced friction compensation anti-disturbance control strategy for improving the speed regulation control performance of a permanent magnet synchronous motor operating in low-speed mode. This is achieved via friction modelling and lumped disturbance compensation by seamlessly integrating extended state observer (ESO) and Kalman filter algorithms. Considering that nonlinear friction torque can not be ignored at low speeds, a piece-wise linearized friction model is first established based on speed estimation of Kalman filter and ESO. Then feed-forward compensation of friction torque and lumped disturbance estimation is conducted to reduce speed fluctuation during load changes at low speeds. Comparative simulation studies in the presence of measurement noises, external disturbances and nonlinear friction torque are conducted to validate the proposed algorithm with improved performance. © The Institution of Engineering & Technology 2023.

关键词： Kalman filters

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Calibration of 3D Single-pixel Imaging systems with a Calibration Field

arXiv

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arXiv 2024年

作者： Ma, Xinyue Wang, Chenxing The School of Automation The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

3D single-pixel imaging (SPI) is a promising imaging technique that can be flexibly applied to various wavebands. The main challenge in 3D SPI is that the calibration usually requires a large number of standard points as references, which are tricky to capture using single-pixel detectors. Conventional solutions involve sophisticated device deployment and cumbersome operations, resulting in hundreds of images needed for calibration. In our work, we construct a Calibration Field (CaliF) to efficiently generate the standard points from one single image. A high accuracy of the CaliF is guaranteed by the technique of deep learning and digital twin. We perform experiments with our new method to verify its validity and accuracy. We believe our work holds great potential in 3D SPI systems or even general imaging systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Calibration

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Real-Time Multi-View Human Pose Estimation system

Real-Time Multi-View Human Pose Estimation System

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yuan Yang Yangang Wang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

We present a highly synchronized multi-view hardware acquisition system that simultaneously enables real-time multi-person pose estimation. We design a hardware synchronizer to achieve multi camera synchronous shooting, with a synchronization latency rate of only 10 −8 seconds. Based on this, we construct a multi-view hardware synchronous acquisition system. This system can be flexibly deployed in various environments to capture moving targets, such as bodies, clothing, hands, etc. Leveraging the distributed computing capabilities of the system, we further develop a multi-view multi-person pose estimation algorithm framework that fulfills real-time requirements and achieves an average frame rate of 40FPS in experimental settings while demonstrating robustness against human motion and occlusion.

关键词： Pose estimation Data acquisition Clothing Cameras Hardware Real-time systems Robustness

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A Data-Driven Modeling and Motion control of Heavy-Load Hydraulic Manipulators via Reversible Transformation

arXiv

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arXiv 2024年

作者： Ma, Dexian Liu, Yirong Liu, Wenbo Zhou, Bo Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Ministry of Education Nanjing210096 China

This work proposes a data-driven modeling and the corresponding hybrid motion control framework for unmanned and automated operation of industrial heavy-load hydraulic manipulator. Rather than the direct use of a neural network black box, we construct a reversible nonlinear model by using multilayer perceptron to approximate dynamics in the physical integrator chain system after reversible transformations. The reversible nonlinear model is trained offline using supervised learning techniques, and the data are obtained from simulations or experiments. Entire hybrid motion control framework consists of the model inversion controller that compensates for the nonlinear dynamics and proportional-derivative controller that enhances the robustness. The stability is proved with Lyapunov theory. Co-simulation and Experiments show the effectiveness of proposed modeling and hybrid control framework. With a commercial 39-ton class hydraulic excavator for motion control tasks, the root mean square error of trajectory tracking error decreases by at least 50% compared to traditional control methods. In addition, by analyzing the system model, the proposed framework can be rapidly applied to different control plants. Copyright © 2024, The Authors. All rights reserved.

关键词： Industrial manipulators

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First attempt of barrier functions for Caputo's fractional-order nonlinear dynamical systems

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Science China(Information Sciences) 2023年第7期66卷 313-314页

作者： Zheren ZHU Pengfei HUANG Xinmin ZHANG Yi CHAI Zhihuan SONG College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology School of Automation Chongqing University Key Laboratory of Complex System Safety and Control(Chongqing University) Ministry of Education

Dear editor, In the past two decades, scholars have begun to use system dynamical models and state motions to study the safety of a system to realize the analysis, diagnosis, and control of system safety. This safety ...

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Study on Self-Organizing Aggregation Method for Massive Flexible Resources and Its Simulation 4

Study on Self-Organizing Aggregation Method for Massive Flex...

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4th International Conference on Advanced Electrical and Energy systems, AEES 2023

作者： Yin, Changwei Ji, Wenlu Ye, Ting Mao, Tingfeng Zhang, Kaifeng Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Power Supply Company of State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

ISBN: (纸本)9798350342659

Distributed flexible resources are developing in the trend of sea quantization. In this situation, the existing resource aggregation methods are facing bottlenecks, and it is difficult to fully exploit the regulation potential of massive flexible resources. In order to achieve efficient and flexible aggregation in the scenario of massive resources, this paper proposes a self-organizing aggregation method for flexible resources based on the social network and simulates the aggregation process under the proposed method based on the multi-agent simulation platform NetLogo. Firstly, this paper outlines the idea of the self-organizing aggregation method for flexible resources, which projects flexible resources from the physical space to the social network space, and realizes flexible aggregation through the interactive attraction between resources in the social network. Secondly, this paper establishes a simulation model for flexible resource self-organizing aggregation based on the NetLogo platform. The model defines four types of agents involved in the self-organizing aggregation process and provides detailed specifications for their attributes and interaction rules. Finally, simulation experiments are designed to verify the rationality of the self-organizing aggregation method and simulation model proposed in this paper. The simulation results show that, following the idea of self-organizing aggregation, massive flexible resources can autonomously and flexibly aggregate through the interaction attraction in the social network due to the incentive of task gain, demonstrating the effectiveness and rationality of the self-organizing aggregation method and the simulation model proposed in this paper. © 2023 IEEE.

关键词： Multi agent systems

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Estimation of Metro Passenger Capacity Based on Passenger-Train Matching Model 3rd

Estimation of Metro Passenger Capacity Based on Passenger-Tr...

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3rd International Conference on Information control, Electrical Engineering, and Rail Transit, ICEERT 2023

作者： Mei, Zhenkun Chen, Beijia Liu, Jiajun Shao, Jiayu Zhang, Ning Suzhou Rail Transit Group Co. Ltd. Jiangsu Suzhou215004 China School of Automation Southeast University Jiangsu Nanjing210096 China Key Laboratory of Measurement and Control of Complex Engineering Systems Ministry of Education Southeast University Jiangsu Nanjing210096 China ITS Engineering Research Center Ministry of Education Southeast University Jiangsu Nanjing211189 China

ISBN: (纸本)9789819788903

In the present scenario of the ‘one-tapin-one-tapout’ operation mode in urban rail transportation, determining passenger travel trajectories is challenging, thereby decreasing the effective counting of passengers on trains. In order to address this issue, a method for calculating passenger capacity on trains was developed by analyzing passenger travel information extracted from AFC data and train timetables. First, this research estimated the components of journey time to infer and reconstruct the passenger's specific spatiotemporal travel trajectory. The passenger-train matching model was then used to assign passengers to specific trains and calculate the passenger load of different trains at each station. At last, it took Suzhou Metro Line 3 as an example and analyzed the spatiotemporal distribution of urban rail transit passenger flow on a single line based on the proposed passenger-train model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Urban transportation

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Magnetic Microrobots Fabricated by Photopolymerization and Assembly

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Cyborg and Bionic systems 2023年第1期4卷 41-46页

作者： Xiyue Liang Yue Zhao Dan Liu Yan Deng Tatsuo Arai Masaru Kojima Xiaoming Liu Key Laboratory of Biomimetic Robots and Systems Ministry of EducationState Key Laboratory of Intelligent Control and Decision of Complex SystemBeijing Advanced Innovation Center for Intelligent Robots and Systemsand School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Center for Neuroscience and Biomedical Engineering The University of Electro-CommunicationsTokyo 182-8585Japan Department of Materials Engineering Science Osaka UniversityOsaka 560-8531Japan

Magnetic soft microrobots have great potential to access narrow spaces and conduct multiple tasks in the biomedical *** now,drug delivery,microsurgery,disease diagnosis,and dredging the blocked blood vessel have been realized by magnetic soft microrobots in vivo or in ***,as the tasks become more and more complex,more functional units have been embedded in the body of the developed magnetic *** magnetic soft microrobots with complex designed geometries,mechanisms,and magnetic orientation are now greatly challenging the fabrication of the magnetic *** this paper,we propose a new method combining photopolymerization and assembly for the fabrication of magnetic soft *** the micro-hand assembly system,magnetic modules with different shapes and materials are firstly arrayed with precise position and orientation ***,the developed photopolymerization system is employed to fix and link these modules with soft *** on the proposed fabrication method,3 kinds of soft magnetic microrobots were fabricated,and the fundamental locomotion was *** believe that the presented fabrication strategy could help accelerate the clinical application of magnetic microrobots.

关键词： Magnetic system precise

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GraspDiff: Grasping Generation for Hand-Object Interaction With Multimodal Guided Diffusion

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IEEE Transactions on Visualization and Computer Graphics 2024年 PP卷 PP-PP页

作者： Zuo, Binghui Zhao, Zimeng Sun, Wenqian Yuan, Xiaohan Yu, Zhipeng Wang, Yangang Southeast University School of Automation Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

Grasping generation holds significant importance in both robotics and AI-generated content. While pure network paradigms based on VAEs or GANs ensure diversity in outcomes, they often fall short of achieving plausibility. Additionally, although those two-step paradigms that first predict contact and then optimize distance yield plausible results, they are always known to be time-consuming. This paper introduces a novel paradigm powered by DDPM, accommodating diverse modalities with varying interaction granularities as its generating conditions, including 3D object, contact affordance, and image content. Our key idea is that the iterative steps inherent to diffusion models can supplant the iterative optimization routines in existing optimization methods, thereby endowing the generated results from our method with both diversity and plausibility. Using the same training data, our paradigm achieves superior generation performance and competitive generation speed compared to optimization-based paradigms. Extensive experiments on both in-domain and out-of-domain objects demonstrate that our method receives significant improvement over the SOTA method. We will release the code for research purposes. © 1995-2012 IEEE.

关键词： 3D modeling

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Fault diagnosis of bearings based on deep separable convolutional neural network and spatial dropout

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Chinese Journal of Aeronautics 2022年第10期35卷 301-312页

作者： Jiqiang ZHANG Xiangwei KONG Xueyi LI Zhiyong HU Liu CHENG Mingzhu YU School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of EducationNortheastern UniversityShenyang 110819China Liaoning Province Key Laboratory of Multidisciplinary Design Optimization of Complex Equipment Northeastern UniversityShenyang 110819China Angang Steel Company Limited Anshan 114021China

Bearing pitting,one of the common faults in mechanical systems,is a research hotspot in both academia and *** fault diagnosis methods for bearings are based on manual experience with low diagnostic *** study proposes a novel bearing fault diagnosis method based on deep separable convolution and spatial dropout *** separable convolution extracts features from the raw bearing vibration signals,during which a 3×1 convolutional kernel with a one-step size selects effective features by adjusting its *** similarity pruning process of the channel convolution and point convolution can reduce the number of parameters and calculation quantities by evaluating the size of the weights and removing the feature maps of smaller *** spatial dropout regularization method focuses on bearing signal fault features,improving the independence between the bearing signal features and enhancing the robustness of the model.A batch normalization algorithm is added to the convolutional layer for gradient explosion control and network stability *** validate the effectiveness of the proposed method,we collect raw vibration signals from bearings in eight different health *** experimental results show that the proposed method can effectively distinguish different pitting faults in the bearings with a better accuracy than that of other typical deep learning methods.

关键词： Batch normalization Convolutional neural network Fault diagnosis Similarity pruning Spatial dropout

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