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检索条件"任意字段=27th International Conference on Automation and Computing, ICAC 2022"

共 231 条记录，以下是1-10 订阅

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2022 27th international conference on automation and computing: Smart Systems and Manufacturing, icac 2022

2022 27th International Conference on Automation and Computi...

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27th international conference on automation and computing, icac 2022

ISBN: (纸本)9781665498074

the proceedings contain 102 papers. the topics discussed include: robotic disassembly and remanufacturing automation;dual quaternion based finite-time tracking control for mechatronic systems with actuation allocation;flexible personnel scheduling in large multi-product unpaced asynchronous assembly lines;3d-multi-layer-multi-representation-maps for short- and long-term mapping and navigation;proof of learning: two novel consensus mechanisms for data validation using blockchain technology in water distribution system;utilizing lexicon-enhanced approach to sensitive information identification;molecular signaling under different transmitting waveform for applied deployments;attribute guided graph convolutional network with stronger generalization for person re-identification;narrow gap tig arc weld process monitoring;and state of charge estimation using extended Kalman filter in electric vehicles.

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2022 IEEE 27th international conference on Emerging Technologies and Factory automation, ETFA 2022

2022 IEEE 27th International Conference on Emerging Technolo...

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27th IEEE international conference on Emerging Technologies and Factory automation, ETFA 2022

ISBN: (纸本)9781665499965

the proceedings contain 270 papers. the topics discussed include: 5G RAN slicing to support reliability in industrial applications;a blueprint of digital twins in high volume production environments using the asset administration shell;a civil protection early warning system to improve the resilience of Adriatic-Ionian territories to natural and man-made risk;a coordination artifact for multi-disciplinary reuse in production systems engineering;a digital twin-based approach performing integrated process planning and scheduling for service-based production;a factory planning and design framework for integrating the digital twin in industry 4.0;a framework for safe and intuitive human-robot interaction for assistant robotics;a graph-based knowledge representation and pattern mining supporting the digital twin creation of existing manufacturing systems;a methodology for classifying data relevance to utilize external data sources in the digital twin;a methodology for creating semantic digital twin models supported by knowledge graphs;and a methodology to select wearable devices for industry 5.0 applications.

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Perspective of self-learning robotics for disassembly automation 27

Perspective of self-learning robotics for disassembly automa...

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27th international conference on automation and computing, icac 2022

作者： Goli, Farzaneh Wang, Yongjing Saadat, Mozafar University of Birmingham Department of Mechanical Engineering United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Increasing attention has been paid to remanufacturing which plays an important role in environmental protection and circular economy. Disassembly is a key operation in remanufacturing, repair, and recycling. Several robotic disassembly developments have shown that the use of robots in disassembly is feasible;however, the programming of robots is usually complex, schedule-based, and time-consuming. Recent research about self-learning robotics and human-robot collaboration have created an opportunity for schedule-free robotics, in which various machine learning and deep learning techniques have been developed. this paper attempts to review the development of self-learning robots with applications in robotic disassembly and remanufacturing. Key algorithms, designs, control methods, and future research directions have been highlighted and analysed. this review paper serves as a useful resource for researchers in the areas of robotics, smart remanufacturing, and disassembly automation. © 2022 IEEE.

关键词： Reinforcement learning

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Adaptive Fixed-time Fuzzy Tracking Control of Uncertain Robot 27

Adaptive Fixed-time Fuzzy Tracking Control of Uncertain Robo...

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27th international conference on automation and computing, icac 2022

作者： Zhou, Beibei Zhu, Chengzhi Jiang, Yiming Guangzhou Jianxin Technology Co. Ltd Guangzhou510640 China South China University of Technology Key Laboratory of Autonomous Systems and Net-worked Control College of Automation Science and Engineering Guangzhou510640 China Hunan University National Engineering Laboratory for Robot Visual Perception and Control Hunan Changsha410082 China

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

We propose a novel fixed-time fuzzy control strategy to achieve the trajectory tracking of the robot systems with uncertainties in this article. the tracking errors of the system can be convergent to a small area around zero with fixed-time convergence rate, combining with the fuzzy logic system and the backstepping technique. Besides, the boundedness of all the closed-loop system signals can be proved under the proposed controller. the superiority performance of the proposed control strategy has been shown by the simulation results. © 2022 IEEE.

关键词： Closed loop systems

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Fixed-time Adaptive Neural Control for Robot Manipulators with Input Saturation and Disturbance 27

Fixed-time Adaptive Neural Control for Robot Manipulators wi...

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27th international conference on automation and computing, icac 2022

作者： Huang, Haiqi Lu, Zhenyu Wang, Ning Yang, Chenguang South China University of Technology College of Automation Science and Engineering Guangzhou510640 China University of the West of England Bristol Robotics Laboratory BristolBS16 1QY United Kingdom

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

A fixed-time adaptive neural network control scheme is designed for an unknown model manipulator system with input saturation and external environment disturbance, so that the system convergence time can be parameterized and not affected by the initial state of the system. the compensation control item is introduced to compensate for external disturbance. the scheme can ensure that the input torque always does not exceed the actuator saturation value and the transient and steady state performance will not significantly degrade. Furthermore, the Incremental Broad Neural Network (IBNN) is used for approximating unknown models with flexible adjustability and high computational efficiency, so it can be applied to scenarios with different control precision requirements. Simulation results verify the effectiveness of the scheme in the above aspects. © 2022 IEEE.

关键词： Computational efficiency

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Real-time Gait Trajectory Prediction Based on Convolutional Neural Network with Multi-head Attention 27

Real-time Gait Trajectory Prediction Based on Convolutional ...

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27th international conference on automation and computing, icac 2022

作者： Yin, Jie Xue, Tao Zhang, Tao Tsinghua University Department of Automation Beijing China

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

the lower limb exoskeleton can effectively improve the ability of users. Accurate gait trajectory prediction can enhance the effect of lower limb exoskeletons. the current gait trajectory prediction methods have the disadvantages of insufficient prediction accuracy and long calculation time. this paper proposes a convolutional neural network model with multi-head attention to predict the gait trajectory. Compared with the widely used recurrent neural network model, the model we proposed in this paper can predict gait trajectory with higher accuracy and shorter calculation time. the error is reduced by up to 21.3% and the average calculation time is reduced by 62.8%. Based on the proposed model, we design a controller of the lower limb exoskeleton to achieve better effects in mixed gait and eliminate the delay. © 2022 IEEE.

关键词： Neural network models

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Hybrid Gait Recognition Method Based on Phase Trajectory 27

Hybrid Gait Recognition Method Based on Phase Trajectory

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27th international conference on automation and computing, icac 2022

作者： Li, Pinjie Xue, Tao Zhang, Tao Wang, Huangang Zhang, Ming Tsinghua University Department of Automation Beijing China Shenzhen International Graduate School Tsinghua University Department of information science and technology Beijing China

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

Gait recognition is critical to the activity monitoring, health management, assistance control of prostheses and exoskeletons, etc. this study aims to improve the gait classification performance on daily hybrid locomotions. We found the hip angle phase trajectories present significantly gait-dependent patterns, whereas the phase patterns show repeated limit cycles for periodic gaits while half-cycles or dots for aperiodic gaits. By converting the gait recognition issue into an image classification problem, we propose to use a convolution neural network (CNN) to learn the gait-dependent phase pattern images. Besides, to enhance the gait transition stability, we further integrate the prior state transition probability with category likelihood via dynamic Bayesian network. the proposed method has been experimented with 6 healthy subjects on standing, sitting, stand-to-sit, sit-to-stand, walking, running, stair ascending, and stair descending gaits. the overall leave-one-out cross-validation accuracy in continuous time is 96.15%. © 2022 IEEE.

关键词： Continuous time systems

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Material Removal Rate Prediction with Phase Sensitive Variables Selection and Phase Partition 27

Material Removal Rate Prediction with Phase Sensitive Variab...

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27th international conference on automation and computing, icac 2022

作者： Lv, Chunpu Zhang, Tao Wang, Huangang Tsinghua University Department of Automation Beijing China

ISBN: (数字)9781665498074

ISBN: (纸本)9781665498074

In the Chemical Mechanical Planarization (CMP) process of the semiconductor industry, high accuracy prediction of Material Removal Rate (MRR) is essential to achieve wafer-to-wafer (W2W) control. therefore, data-driven Virtual Metrology (VM) methods for MRR prediction have received much attention. Traditional methods focus on extracting features from raw data along the time dimension. However, a CMP process is a batch process with multi-phase and uneven-length characteristics, and different phases have different operating points and data correlations. In this paper, a novel VM method based on phase partition and feature selection is proposed. the phase-sensitive variables are selected by a wrapped approach and combined with a clustering algorithm for phase partition. After extracting the phase features, a suitable subset of features is selected using multiple feature selection methods and input to a regressor for prediction. the results in the PHM16 Dataset validate the effectiveness of the proposed method, which has higher prediction accuracy compared with the methods without phase partition. © 2022 IEEE.

关键词： Feature Selection

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Parametric Geoinformational Models 27

Parametric Geoinformational Models

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27th international conference on Soft computing and Measurements, SCM 2024

作者： Verkhova, Galina V. Akimov, Sergej V. Department of Intelligent Automation and Control Systems Saint-Petersburg Russia

ISBN: (纸本)9798350363708

A methodology for parametric multi-aspect models of spatially distributed objects is presented. the proposed models make it possible to present attribute information of hierarchical spatially distributed objects and geosystems, taking into account the relationships between hierarchy levels, as well as the values of expert parameters and parameters obtained as a result of monitoring. Another important feature of parametric geographic information models is their support for generalization and the ability to use them to create multi-scale objects. © 2024 IEEE.

关键词： Information theory

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Application of Kalman Filter in Intelligent Control Systems of Electric Drives of Industrial Systems 27

Application of Kalman Filter in Intelligent Control Systems ...

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27th international conference on Soft computing and Measurements, SCM 2024

作者： Belov, Alexander M. Belov, Mihail P. Saint-Petersburg Electrotechnical University 'LETI' Department of Robotics and Automation of Industrial Processes Saint-Petersburg Russia

ISBN: (纸本)9798350363708

In industrial systems, automated electric drives are subjected to various internal disturbances as well as external disturbances. these disturbing influences do not allow to provide appropriate control accuracy and necessary dynamic characteristics. therefore, the paper discusses the application of Kalman filter together with neural controllers in multi-electro-drive industrial systems in order to compensate internal and external disturbances and to achieve the required dynamic characteristics. © 2024 IEEE.

关键词： Kalman filters

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