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2nd International Conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2022

作者： Liu, Yang Zhang, Tianshi Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665459280

ISBN: (纸本)9781665459280

Industrial big data analysis is an important approach to explore the essence of industrial production processes. Traditional keyword retrieval and semantic retrieval are difficult to adapt to the industrial manufacturing systems with the characteristics of strong coupling of business associations. Therefore, according to the characteristics of the association in the industrial production system, an association retrieval model for the industrial production system is proposed in this paper. Firstly, the industrial Internet of things system is analyzed and abstracted, and the key factors of correlation retrieval are derived;then through the analysis of the relationship between key factors, the invalid relationship is screened out, the correlation relationship with practical significance is obtained, and the establishment of the relevance retrieval model is completed. Finally, the feasibility and effectiveness of the association retrieval model are verified by actual industrial scene data. © 2022 IEEE.

关键词： Manufacture

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Design of an Acupuncture Robot with Vision-Guided Positioning and Force Compliance control 6

Design of an Acupuncture Robot with Vision-Guided Positionin...

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6th International Symposium on robotics and Intelligent Manufacturing Technology, ISRIMT 2024

作者： Chen, Zhengtao Li, Bochen Feng, Yanhao Chen, Genliang Wang, Hao Shanghai Jiao Tong University Shanghai Key Laboratory of Digital Manufacturing for Thin-Walled Structures Shanghai China Meta Robotics Institute Shanghai Jiao Tong University Shanghai China Shanghai Jiao Tong University State Key Laboratory of Mechanical Systems and Vibration Shanghai China

ISBN: (纸本)9798331528942

Acupuncture is a classic treatment method in traditional Chinese medicine. At present, it mainly relies on experienced doctors for manual treatment. The inheritance of skills and the guarantee of treatment effects require lots of training to guarantee, which is far from meeting needs. In this paper, an acupuncture robot system was designed to ensure the accuracy of acupoint positioning and safety during needle insertion, making robot-assisted acupuncture treatment a feasible alternative. The acupuncture robot has an acupoint marking and visual guidance system. According to the location of the acupoints accurately marked by the doctor on the patient's 3D reconstructed model, the robot is accurately guided to perform acupuncture treatment. The positioning error of this system is within 1.5mm, which meets the needs of acupuncture. In addition, a terminal needle-punching manipulator with compliant needle insertion force control, needle insertion depth feedback, and continuous needle insertion functions is designed. Through the closed-loop control of the needle-punching manipulator, the safety and accuracy of the acupuncture robot are fully guaranteed. Finally, an acupuncture experiment was designed to verify the accuracy and safety of the acupuncture robot. © 2024 IEEE.

关键词： Acupuncture

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An analysis method of industrial data relationship based on business context 3

An analysis method of industrial data relationship based on ...

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3rd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2022

作者： Liu, Yang Zhang, Tianshi Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

Industrial big data processing is an important support for improving industrial production efficiency. Because industrial big data involves complex business logic in production scenarios, there is a widespread problem that the relationship between data is difficult to understand. Therefore, this paper proposes a relational analysis method of industrial data based on business context. Firstly, a semantic data dictionary is established according to the production business process, and then a data object recognition model based on deep learning is trained;then a context-based automatic association method of industrial data relations is proposed;finally, the experimental verification is carried out on the actual production data, and the results show that The method in this paper is effective in improving the relationship analysis of industrial data. © 2022 IEEE.

关键词： Big data

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Research on Sensorless control of Pulse Generator based on Sliding Mode Observer

Research on Sensorless Control of Pulse Generator based on S...

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2023 International Conference on Artificial Intelligence and Automation control, AIAC 2023

作者： Zhang, Hui Wu, Zhiguo Jin, Bopi Yang, Shengxuan Yin, Guoliang Shenyang Jianzhu University College of Electrical and Control Engineering Shenyang China College of Electrical and Control Engineering Shenyang Jianzhu University State Key Laboratory of Robotics Shenyang Institute of Automation Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Institutes of Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China

ISBN: (纸本)9798350383805

To address the problems of chattering and slow response in the sliding mode control system of surface-mounted permanent magnet synchronous motor (SPMSM), a novel sliding mode controller combined with an enhanced sliding mode observer is proposed. A new reaching law of sliding mode is designed, which uses the tanh function as the switching function of the control system to smooth the switching process. The terminal attractor is introduced to improve the convergence speed and control quality of the system. An improved sliding mode observer is developed, which replaces the sign function with a continuous function, compensates for the observation error, reduces the chattering effect, and improves the observation accuracy. A simulation model of double closed-loop speed control system based on the proposed sliding mode controller and observer is established, and a simulation experiment is conducted to compare it with the PI control system and the sliding mode control system based on exponential reaching law. The simulation results show that the proposed control strategy can effectively diminish the chattering effect, enhance the system convergence, and better track the given signal. © 2023 IEEE.

关键词： Sliding mode control

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An Adaptive Feedforward Optimization Mechanism for Improving Industrial Robots Trajectory Tracking Performance through Iterative Learning

An Adaptive Feedforward Optimization Mechanism for Improving...

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robotics, control and Automation (ICRCA), International Conference on

作者： Chengzhi Wang Sikai Zhao Tianjiao Zheng Hegao Cai Jie Zhao Yanhe Zhu State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

This paper presents an adaptive feedforward optimization method based on iterative learning control mechanism, improving trajectory tracking accuracy from trial to trail. Conventional feedforward control researches focus on the precise prediction and compensation of torques, either by means of dynamic modelling and parameter identification or by data-driven approaches. However, there exists unpredictable time-delay for torques to work. The proposed method takes the previously less-concerned velocity feedforward part of the servo control system into consideration, and a self-adaptive fine-tuning mechanism is designed and established. The error measurement and feedforward optimization processes are integrated into an iterative learning framework to obtain efficiency and precision. The effectiveness of proposed method is validated by physical experiments on an EFORT ER15 industrial robot, and an averagely 90.71% error reduction is witnessed.

关键词： Accuracy Torque Parameter estimation Trajectory tracking Service robots Predictive models Industrial robots Feedforward systems Servosystems Tuning

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Construction Methods Based on Minimum Weight Distribution for Polar Codes with Successive Cancellation List Decoding

arXiv

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arXiv 2023年

作者： Piao, Jinnan Li, Dong Liu, Jindi Yu, Xueting Li, Zhibo Yang, Ming Zeng, Peng The State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China The Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China

Minimum weight distribution (MWD) is an important metric to calculate the first term of union bound called minimum weight union bound (MWUB). In this paper, we first prove the maximum likelihood (ML) performance approaches MWUB as signal-to-noise ratio (SNR) goes to infinity and provide the deviation when MWD and SNR are given. Then, we propose a nested reliability sequence, namely MWD sequence, to construct polar codes independently of channel information. In the sequence, synthetic channels are sorted by partial MWD which is used to evaluate the influence of information bit on MWD and we prove the MWD sequence is the optimum sequence evaluated by MWUB for polar codes obeying partial order. Finally, we introduce an entropy constraint to establish a relationship between list size and MWUB and propose a heuristic construction method named entropy constraint bit-swapping (ECBS) algorithm, where we initialize information set by the MWD sequence and gradually swap information bit and frozen bit to satisfy the entropy constraint. The simulation results show the MWD sequence is more suitable for constructing polar codes with short code length than the polar sequence in 5G and the ECBS algorithm can improve MWD to show better performance as list size increases. Copyright © 2023, The Authors. All rights reserved.

关键词： Signal to noise ratio

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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Data-Driven Dynamics Modeling of Miniature Robotic Blimps Using Neural ODEs With Parameter Auto-Tuning

arXiv

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arXiv 2024年

作者： Zhu, Yongjian Cheng, Hao Zhang, Feitian State Key Laboratory of Turbulence and Complex Systems the Robotics and Control Laboratory Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China

Miniature robotic blimps, as one type of lighter-than-air aerial vehicles, have attracted increasing attention in the science and engineering community for their enhanced safety, extended endurance, and quieter operation compared to quadrotors. Accurately modeling the dynamics of these robotic blimps poses a significant challenge due to the complex aerodynamics stemming from their large lifting bodies. Traditional first-principle models have difficulty obtaining accurate aerodynamic parameters and often overlook high-order nonlinearities, thus coming to their limit in modeling the motion dynamics of miniature robotic blimps. To tackle this challenge, this letter proposes the Auto-tuning Blimp-oriented Neural Ordinary Differential Equation method (ABNODE), a data-driven approach that integrates first-principle and neural network modeling. Spiraling motion experiments of robotic blimps are conducted, comparing the ABNODE with first-principle and other data-driven benchmark models, the results of which demonstrate the effectiveness of the proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Airships

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Comparison of Three Data-Driven networked Predictive control Methods for a Class of Nonlinear systems

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1714-1716页

作者： Zhong-Hua Pang Xue-Ying Zhao Jian Sun Yuntao Shi Guo-Ping Liu the Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China the State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China the Center for Control Science and Technology Southern University of Science and TechnologyShenzhen 518055China

Dear Editor,In this letter,in order to deal with random network delays and packet losses in a class of networked nonlinear systems,three data-driven networked predictive control methods are *** closed-loop systems and... 详细信息

关键词： letter Nonlinear nonlinear

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RESEARCH ON THE PID PARAMETER SELF-TUNING OF THE PRESSURIZER control SYSTEM OF NUCLEAR POWER PLANT 29

RESEARCH ON THE PID PARAMETER SELF-TUNING OF THE PRESSURIZER...

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2022 29th International Conference on Nuclear Engineering, ICONE 2022

作者： Wang, Hongrui Xing, Kunpeng Zou, Tao Yang, Zhijia Wang, Jingyang Zhang, Pengbin State Key Laboratory of Robotics Key Laboratory of Networked Control System Institutes for Robotics and Intelligent Manufacturing Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China China Nuclear Power Engineering Co. Ltd Shenzhen China College of Mechanical and Electrical Engineering Guangzhou University Guangzhou China Key Laboratory of Networked Control System Institutes for Robotics and Intelligent Manufacturing Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9780791886373

The pressurizer is an essential part of the safe operation of the nuclear power plant. It contains both the steam phase and the liquid phase, which requires simultaneous control of the pressure and water level, and the control system is strongly coupled. When using the PID control method, it is difficult to tune the parameters, and the difficulty is exacerbated when the set value fluctuates. This paper aims at the multi-input and multioutput pressurizer control system, based on the particle swarm optimization to realize the PID controller parameters self-tuning, adopting the time and absolute error integral as the fitness function to evaluate the merits of the PID parameters, and constantly iterating to update and obtain the PID parameters that better satisfy the current working conditions. For coupled pressurizer control systems, the PID parameter tuning method using particle swarm optimization algorithms can give a group of PID controller parameters that make the system operation stable despite the frequent fluctuation of the set value, and compared with the traditional PID controller parameter tuning method, this method can realize the PID parameter self-tuning, eliminating the trouble of manual tuning. Copyright © 2022 by ASME.

关键词： Nuclear power plants

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