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2019 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019

作者： Martinov, G. Issa, A. Martinova, L. Institute of Automation and Robotics Dept. Computer Control Systems Moscow Russia

ISBN: (纸本)9781728100616

The diverse requirements of customers in automation systems increase the need for improved adaptability, flexibility and of simplicity production processes. which creates new horizons for modern production systems. Fortunately, the achievements of the Industry 4.0 (fourth industrial revolution) have provided many solutions to these problems. In this study, an OPC UA-based solution is proposed for monitoring the working process of CAN servo drives. By integrating C++ based OPC UA libraries to implement common OPC UA functionality and developing protocol of interaction between the kernel of CNC system and OPC UA server. The aim of this work is to ensure the connection mechanism between OPC UA Server of CNC system and OPC UA clients which are currently existed on the market. This flexible model allows users to remotely tune and set up CAN servo drives and monitor their work. © 2019 IEEE.

关键词： Digital storage

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Reinforcement Learning with Large Language Model for Hybrid Disassembly Lines in Remanufacturing Contexts

Reinforcement Learning with Large Language Model for Hybrid ...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Peng Ji Xi Wang Guo Jiacun Wang Weitian Wang Shu Jin Qin Ying Tang Qi Kang College of Information and Control Engineering Liaoning Petrochemical University Fushun China Dept of Comp. Sci. and Soft. Eng. Monmouth University W. Long Branch NJ USA Collaborative Robotics and Smart Systems Laboratory (CRoSS Lab) Montclair State University Montclair NJ USA College of Economics and Management Shangqiu Normal University Shangqiu China Electrical and Computer Engineering Rowan University Glassboro New Jersey USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Large language models (LLM), ChatGPT is making substantial impact across various fields. This study for the first time presents a novel approach to the hybrid disassembly line balancing problem using LLM and reinforcement learning algorithms in remanufacturing contexts. The problem is divided into two sub-stages. LLM is innovatively used to capture a disassembly sequence well in the first stage, while reinforcement learning is utilized to address the problem in the second stage. Upon comparing the performance with and without LLM, the proposed approach significantly reduces the trial-and-error space and achieves faster convergence to achieve the desired solution. Future work of this study is also discussed.

关键词： computer aided software engineering Automation Large language models Reinforcement learning Chatbots Convergence

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Learning-based control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy

Learning-based Control for PMSM Using Distributed Gaussian P...

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Annual Conference of Industrial Electronics Society

作者： Zhenxiao Yin Xiaobing Dai Zewen Yang Yang Shen Georges Hattab Hang Zhao Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Chair of Information-oriented Control Technical University of Munich Munich Germany Center for Artificial Intelligence in Public Health Research (ZKI-PH) Robert Koch Institute Berlin Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Hong Kong China

The growing demand for accurate control in varying and unknown environments has sparked a corresponding increase in the requirements for power supply components, including permanent magnet synchronous motors (PMSMs). To infer the unknown part of the system, machine learning techniques are widely employed, especially Gaussian process regression (GPR) due to its flexibility of continuous system modeling and its guaranteed performance. For practical implementation, distributed GPR is adopted to alleviate the high computational complexity. However, the study of distributed GPR from a control perspective remains an open problem. In this paper, a control-aware optimal aggregation strategy of distributed GPR for PMSMs is proposed based on the Lyapunov stability theory. This strategy exclusively leverages the posterior mean, thereby obviating the need for computationally intensive calculations associated with posterior variance in alternative approaches. Moreover, the straightforward calculation process of our proposed strategy lends itself to seamless implementation in high-frequency PMSM control. The effectiveness of the proposed strategy is demonstrated in the simulations.

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Phase-Based Quantification of Sports Performance Metrics Using a Smart IoT Sensor

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IEEE Internet of Things Journal 2023年第18期10卷 15900-15911页

作者： Chen, Meng Szu, Hui Fang Lin, Hsin Yen Liu, Yifan Chan, Ho-Yin Wang, Yufan Zhao, Yuliang Zhang, Guanglie Yao, Jeffrey Da-Jeng Li, Wen Jung National Tsing Hua University Physical Education Office Hsinchu City300 Taiwan Kla Corporation Tainan City744 Taiwan Michigan State University Department of Electronic and Computer Engineering East LansingMI48824 United States Shanghai Jiao Tong University School of Mechanical Engineering Department of Industrial Engineering and Management Shanghai200240 China Northeastern University at Qinhuangdao Hebei Key Lab. of Micro-Nano Prec. Optical Sensing and Msrmt. Technol. Sch. of Control Engineering Qinhuangdao066004 China City University of Hong Kong Department of Mechanical Engineering Kowloon Tong Hong Kong City University of Hong Kong Shenzhen Research Institute CASŰCityU Joint Laboratory for Robotics Shenzhen518057 China National Tsing Hua University Department of Power Mechanical Engineering Hsinchu City300 Taiwan

Sports performance is often judged based on the results of a series of motions rather than observing and analyzing the detailed sequential motions that lead to the results. Hence, subjective feedback from the coaches is often ineffective in improving player performance. In this work, we custom-built a smart Internet of Things wristband motion sensor to implement data-based sports performance evaluation. A phase-based feature selection method is also proposed to assess the athletes' sequential detailed motion for selected sport activities. To demonstrate the merits of this technology, we quantified the quality of the sequential motions of a specific type of volleyball serve by analyzing 183 samples of motion data obtained from a total of 18 players. The general skill levels (i.e., elite, subelite, and amateur) of the players were identified by machine learning algorithms, with accuracies of up to 95%. Moreover, we adopted biomechanical principles to extract 11 motion-related performance metrics from various phases of the players' serve motion. We identified the distributions of these metrics across different skill levels and found eight key metrics that were highly correlated to the skill level of a players. We suggest that these metric distributions can be used as a reference for providing feedback to the coaches and players, to improve a player's skill in the future. This phased-based analysis method can potentially be applied across many sports to increase the effectiveness of athletes' training. © 2014 IEEE.

关键词： Internet of things

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Flight demonstrations of lunar cubesat technologies developed for clps

Flight demonstrations of lunar cubesat technologies develope...

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Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2020

作者： Singh, Hunter Huang, Calvin Coble, Kyle Yuan, Christine University of Colorado Boulder United States Pasadena City College Computer Science United States KTH Royal Institute of Technology Systems Control and Robotics Sweden Cornell University Mechanical Engineering United States

ISBN: (纸本)9781624106088

During the summer of 2020, students under the Innovation to Flight (i2F) program will be performing flight demonstrations of lunar CubeSat technologies which include navigation and communication. These Earth-bound flight demonstrations are aimed to test flight-critical technology and hardware that will fly to the Moon utilizing NASA’s Commercial Lunar Payload Services (CLPS). Specifically, a strategic partnership with Qualcomm has opened the door to utilizing Qualcomm’s Modal AI chips on custom boards that will provide both telecommunications, navigation and command and data handling (C&DH) abilities. The i2F team performed the first high altitude near-space environmental testing of the basic Qualcomm Snapdragon system in August of 2019 by utilizing the Zephyrus High Altitude Balloon (HAB) platform that i2F developed in 2017. The flight demonstrations for 2020 will be specifically testing the updated Qualcomm NavComm and C&DH systems ability to provide clocking and positioning to ground based assets at long-range systems testing. Autonomous ground robotics relayed data to lunar analog astronauts at the facility and using the ModalAI board performed visual navigation pushing lunar simulant into gravity filtration systems for processing. The CRADLE (California Research Analog for Deepspace and Lunar Exploration) analogue is a test site in the Mojave Desert that is a 1.5-hour drive from Los Angeles and has analogous features to lunar craters and crevices. The team will present the results of the experiment and next steps in working with the Qualcomm chip in cubesat platforms. University of Colorado Boulder advisor Scott Palo is working with students to provide an achitecture cable of supporting Atemis missions as well as commercial robotics on the moon. © 2020 The MITRE Corporation. All Rights Reserved.

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Exploiting the Intrinsic Neighborhood Semantic Structure for Domain Adaptation in EEG-based Emotion Recognition

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IEEE Transactions on Affective Computing 2025年

作者： Yang, Yi Wang, Ze Song, Yu Jia, Ziyu Wang, Boyu Jung, Tzyy-Ping Wan, Feng Macau University of Science and Technology Macao Centre for Mathematical Sciences Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovation Engineering 999078 China Tianjin University of Technology School of Electrical Engineering and Automation Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin300384 China Chinese Academy of Sciences Beijing Key Laboratory of Brainnetome and Brain-Computer Interface and Brainnetome Center Institute of Automation Beijing100045 China Western University Department of Computer Science Brain Mind Institute LondonONN6A 3K7 Canada University of California at San Diego Swartz Center for Computational Neuroscience Institute for Neural Computation La Jolla CA92093 United States University of Macau Department of Electrical and Computer Engineering Faculty of Science and Technology China University of Macau Centre for Cognitive and Brain Sciences Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation 999078 China

Due to the inherent non-stationarity and individual differences present in electroencephalogram (EEG) signals, developing a generalizable model that performs well on new subjects is challenging in EEG-based emotion recognition. Most existing domain adaptation (DA) methods typically mitigate these discrepancies by aligning the marginal distributions of domain feature representations. However, when there is a significant difference in the class-conditional distribution between domain features and labels, the domain-invariant features learned by aligning marginal distributions may have limited discriminative ability for unlabeled target instances or even prove counterproductive. To address this issue, we propose a Neighborhood Semantic Aware Learning-based Dynamic Graph Attention Convolution (NSAL-DGAT) approach that learns target semantic information by considering the inter-domain semantic topological structure, thereby improving classifier adaptation for target instances. Specifically, the proposed NSAL framework is designed to capitalize on the insight that after domain feature alignment, some target samples and their neighboring source samples exhibit similar semantics. By leveraging the neighborhood topological structure, we extract and incorporate semantic target features to train a more transferable classifier. Besides, we implement an entropy weighting mechanism to emphasize representative target semantic information, encouraging target instances to prioritize high-confidence individuals within the source neighborhood. We have conducted extensive experiments on the public SEED dataset and our collected the Hearing-Impaired EEG Dataset (HIED). The experimental results underscore the efficacy of our proposed NSAL-DGAT approach, showcasing state-of-the-art accuracy in subject-dependent as well as subject-independent scenarios. The source code is available at https://***/YYingDL/NSAL-DGAT. © 2010-2012 IEEE.

关键词： Speech analysis

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

Optical Evanescent Field for Direct Observation of Sub-100nm...

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robotics, Engineering, Science, and Technology (RESTCON), International Conference on

作者： Panart Khajornrungruang Thitipat Permpatdechakul Keisuke Suzuki Aran Blattler Yutaka Terayama Daiki Goto Pipat Phaisalpanumas Natthaphon Bun-Athuek Amornphun Phunopas Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Mechanical Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Mechanical Information Science and Technology Division Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Production and Robotics Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Mechanical Science and Technology Course Kyushu Institute of Technology Iizuka-Shi Fukuoka Japan Dept. of Industiral Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand Dept. of Mechanical Engineering Technology College of Industrial Technology King Mongkut’s University of Technology North Bangkok Bangsue Bangkok Thailand

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.

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Tactile-Based Object Pose Estimation Employing Extended Kalman Filter

Tactile-Based Object Pose Estimation Employing Extended Kalm...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Qiguang Lin Chaojie Yan Qiang Li Yonggen Ling Yu Zheng Wangwei Lee Zhaoliang Wan Bidan Huang Xiaofeng Liu Jiangsu Key laboratory of Special Robotic Technology College of IoT Engineering Hohai University Changzhou Jiangsu P.R. China State Key Laboratory of Industrial Control and Technology Zhejiang University Institute of Cyber-System and Control Hangzhou P.R. China Neuroinformatics Group Center for Cognitive Interaction Technology (CITEC) Bielefeld University Bielefeld Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou P.R.China

In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the estimation of the object's pose using an Extended Kalman Filter (EKF) based approach. We defined and derived the state and measurement equations, as well as evaluated the estimation accuracy in grasping tasks. The approach is able to effectively account for the pose transition caused by tactile pushing, and the mapping from the object's pose to the contact position and normal direction as measured by the tactile sensor. The method was evaluated in multiple grasping experiments in simulation scenarios. Results show that the estimation can converge towards the ground truth in a relatively short period of time, with displacement and rotation errors remaining within acceptable levels. This new method has the potential to improve the accuracy and reliability of robotic grasping and manipulation tasks.

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Stabilization with Zero Location Constraints for Delay-Based Non-collocated Vibration Suppression ⁎

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IFAC-PapersOnLine 2021年第18期54卷 121-126页

作者： Haik Silm Wim Michiels Tomáš Vyhlídal Departement of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

A generally applicable design of non-collocated vibration absorption by a delayed resonator is proposed. It is grounded in the direct assignment of imaginary axis zeros of the transfer function between the periodic disturbance force and the target. We show that these transmission zeros are characterized as eigenvalues of a delay differential-algebraic system. Furthermore, a stabilizing local controller is added to the setup in order to widen the range of admissible vibration frequencies. These design requirements are translated into an optimization problem of the spectral abscissa function subjected to zero location constraints. The presented approach and algorithm are validated by a simulation on a three body lumped mass-spring system.

关键词： Vibration control Delayed resonator Transmission zeros Stability Spectral method

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Development of Motion controller Based on ARM Microcomputers by Supporting Different Strategies of controlling CAN Servo Drives

Development of Motion Controller Based on ARM Microcomputers...

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2019 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019

作者： Martinov, G. Lyubimov, A. Khoury, A.A. MSTU STANKIN Institute of Automation and Robotics Dept. Computer Control Systems Moscow Russia

ISBN: (纸本)9781728100616

All types of servo step drives motion controllers should guarantee the accuracy of control at all possible rotation speeds taking into consideration the application field of servo drive. Depending on the implementation of servo drives and dividing rotation speed into two ranges low speeds and high speeds, when it's important to have higher rotation speeds (using servo drive as spindle) the motion controller will use speed controlling mode but when it's important to use small values of rotation speeds (using servo drive as feed drive) then it's better to use position controlling mode to ensure the accuracy of the position and minimize the value of errors. Also, it is evidently that the traffic load on CAN bus will affect the stability and the accuracy of controlling CAN servo step drives. The aim of this work is to develop a motion controller that supports dynamically change of controlling strategies of CAN servo step drives depending on rotation speed, additionally will clarify how to reduce CAN bus traffic load. © 2019 IEEE.

关键词： Speed

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