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2023 Power Electronics and Power System Conference, PEPSC 2023

作者： Wang, Jian Xu, Hui Luo, Chuanxian Zhang, Jing Cheng, Lin Yang, Yi Chang, Haoxin State Grid Corporation of China State Grid Equipment Department Beijing China Wuhan Nari Co Ltd. State Grid Electric Power Research Institute Nari Group Corporation State Grid Electric Power Research Institute Wuhan China State Grid Shandong Electric Power Research Institute Ji'nan China School of Electrical Engineering and Automation Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9798350341294

As the intelligence and scale of power equipment continue to increase, the requirements for reliability and safety are also getting higher and higher. Therefore, condition monitoring and data cleaning of power equipment status have become the focus of attention. In this paper, the current research status of power equipment condition monitoring data cleaning methods is reviewed. First, the extraction method and characteristics of monitoring data are introduced, and then the basic cleaning process and common cleaning methods of monitoring data are given. Finally, two types of data cleaning algorithms based on mathematical statistics and artificial intelligence are compared, and it is pointed out that existing problems and future development trends in this field. This review provides a reference for the research on power equipment condition monitoring data cleaning methods, and provides guidance and inspiration for researchers and engineers in related fields. © 2023 IEEE.

关键词： Condition monitoring

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Analyzing Risk Level from RoI and VoI for Robust Data Privacy using Fuzzy Inference System

Analyzing Risk Level from RoI and VoI for Robust Data Privac...

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International Conference on robotics,electrical and Signal Processing Techniques (ICREST)

作者： Rabab Khan Rongon M. Akhtaruzzaman Krishna Das Shekh Tanjil Sharif Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh International University of Business Agriculture and Technology (IUBAT) Dhaka Bangladesh

ISBN: (数字)9798331530952

ISBN: (纸本)9798331530969

In the modern digital environment, securing data privacy has become increasingly critical as organizations confront rising threats from cyber-attacks and data breaches. To safeguard sensitive information, businesses must invest in robust data protection measures, yet balancing these investments with their potential benefits remains challenging. This research addresses this issue by proposing a novel framework that integrates Return on Investment (RoI) and Value of Information (VoI) within a Fuzzy Inference System (FIS) to assess data privacy risks effectively. RoI measures the financial return relative to the cost of data protection investments, indicating the economic value derived from such measures. VoI, on the other hand, evaluates the worth of the information protected by these investments, reflecting its impact on decision-making and operational efficiency. By employing a FIS, which accommodates uncertainties and imprecise data, this framework provides a nuanced approach to risk assessment, enabling organizations to optimize their data privacy strategies. The integration of RoI and VoI within the FIS allows for a comprehensive evaluation of risk levels, facilitating more informed decision-making and improved risk management. This research aims to enhance data privacy practices by offering a methodical and adaptable tool for evaluating and balancing investments in data protection.

关键词： Fuzzy logic Analytical models Uncertainty Decision making Data protection Signal processing algorithms Organizations Mathematical models Risk management Investment

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Adaptive Control of Euler-Lagrange Systems under Time-varying State Constraints without a Priori Bounded Uncertainty

arXiv

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arXiv 2023年

作者： Sankaranarayanan, Viswa Narayanan Satpute, Sumeet Gajanan Roy, Spandan Nikolakopoulos, George Robotics and Artificial Intelligence Group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden Robotics Research Center International Institute of Information Technology Hyderabad India

In this article, a novel adaptive controller is designed for Euler-Lagrangian systems under predefined time-varying state constraints. The proposed controller could achieve this objective without a priori knowledge of system parameters and, crucially, of state-dependent uncertainties. The closed-loop stability is verified using the Lyapunov method, while the overall efficacy of the proposed scheme is verified using a simulated robotic arm compared to the state of the art. © 2023, CC BY-NC-ND.

关键词： Lyapunov methods

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Skeleton-Based Multi-Stream Adaptive Graph Convolutional Network for Indoor Scene Action Recognition

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Net...

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2023 China automation Congress, CAC 2023

作者： Li, Jiazhuo Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru The School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China The Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada The Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland The Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey The Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798350303759

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results. © 2023 IEEE.

关键词： Convolution

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Human-Robot Interaction Control for Multi-Mode Exosuit with Reinforcement Learning

Human-Robot Interaction Control for Multi-Mode Exosuit with ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Kaizhen Huang Jiajun Xu Tianyi Zhang Mengcheng Zhao Aihong Ji Guoli Song Youfu Li College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Nanjing China State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang China Department of Mechanical Engineering City University of Hong Kong Hong Kong SAR China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Soft exoskeleton robots have promising potential in walking assistance with comfortable wearing experience. In this study, an exosuit equipped with a twisted string actuator (TSA) is developed to provide powerful driving force and diverse operating modes for hemiplegic patients in daily life. It is challenging to establish the human-robot coupling dynamic model due to the soft structure of the exosuit and tight coupling, precise control and effective assistance are difficult to guaranteed in current exosuits. Considering the impedance characteristics of human-robot interaction, an adaptive impedance control method based on reinforcement learning (RL) is proposed, where human motion intention is utilized to optimize impedance parameters and adjust the robot's operating mode. A nonlinear disturbance observer is proposed to compensate for the effects of model estimation errors, joint friction, and external disturbances. Experimental verification demonstrates the effectiveness and superiority of the robotic system.

关键词： Legged locomotion Couplings Adaptation models Visualization Heuristic algorithms Human-robot interaction Reinforcement learning Sensor systems Impedance Intelligent sensors

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An Enhanced Data-Driven Model for Lithium-Ion Battery State-of-Health Estimation with Optimized Features and Prior Knowledge

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Automotive Innovation 2022年第2期5卷 134-145页

作者： Huanyang Huang Jinhao Meng Yuhong Wang Lei Cai Jichang Peng Ji Wu Qian Xiao Tianqi Liu Remus Teodorescu College of Electrical Engineering Sichuan UniversityChengduChina Faculty of Computer Science and Engineering Shanxi Key Laboratory for Network Computing and Security TechnologyXi’an University of TechnologyXi’anChina Smart Grid Research Institute Nanjing Institute of TechnologyNanjingChina Department of Automation University of Science and Technology of ChinaHefeiChina Key Laboratory of Smart Grid of Ministry of Education Tianjin UniversityTianjinChina Department of Energy Technology Aalborg University9220 AalborgDenmark

In the long-term prediction of battery degradation,the data-driven method has great potential with historical data recorded by the battery management *** paper proposes an enhanced data-driven model for Lithium-ion(Li-ion)battery state of health(SOH)estimation with a superior modeling procedure and optimized *** Gaussian process regression(GPR)method is adopted to establish the data-driven estimator,which enables Li-ion battery SOH estimation with the uncertainty level.A novel kernel function,with the prior knowledge of Li-ion battery degradation,is then introduced to improve the mod-eling capability of the *** for the features,a two-stage processing structure is proposed to find a suitable partial charging voltage profile with high *** the first stage,an optimal partial charging voltage is selected by the grid search;while in the second stage,the principal component analysis is conducted to increase both estimation accuracy and computing *** of the proposed method are validated on two datasets from different Li-ion batteries:Compared with other methods,the proposed method can achieve the same accuracy level in the Oxford dataset;while in Maryland dataset,the mean absolute error,the root-mean-squared error,and the maximum error are at least improved by 16.36%,32.43%,and 45.46%,respectively.

关键词： Li-ion battery State of health Gaussian process regression Kernel function Feature optimization

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Plate Shape Prediction Based on Data-Driven in Roll Quenching Process

Plate Shape Prediction Based on Data-Driven in Roll Quenchin...

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2023 China automation Congress, CAC 2023

作者： Hu, Liu Chen, Luefeng Hu, Jie Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University The Department of Computer Engineering Istanbul Sariyer34396 Turkey Tokyo Institute of Technology Tokyo Yokohama226-8502 Japan

ISBN: (纸本)9798350303759

In the process of steel plate production, predicting the plate shape is of great significance for producing high-quality and consistently stable plate shapes. This paper presents a model that predicts both the defect types and flatness of the plate, providing theoretical support for setting process parameters in roller quenching production. First, the parameters of the quenching process are analyzed to identify their characteristics. Then, the K-Means clustering algorithm and correlation analysis are employed to process the quenching process parameters. A gradient boosting decision tree (GBDT) model is used to predict the defect types and flatness of the steel plates. Finally, industrial production data is utilized for experimental validation. The obtained experimental results verify the reliability of the proposed method. © 2023 IEEE.

关键词： Decision trees

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Dynamic Characterization and Phenomenological Modelling of Customizable Pneumatic Artificial Muscle 7

Dynamic Characterization and Phenomenological Modelling of C...

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7th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2021

作者： Arora, Aman Sarkar, Debadrata Sen, Soumen Kumar, Amit Roy, Shibendu Shekhar National Institue of Technology Durgapur Department of Mehcanical Engineering Durgapur India Robotics and Automation Group CSIR-Central Mechanical Engineering Research Institute Durgapur Durgapur India

ISBN: (纸本)9781665428491

Pneumatic Artificial Muscles (PAMs) are gaining popularity over traditional actuators in applications where the requirement are high force density, low mass, biological muscle like characteristics, etc,. Especially in applications related to Human Robot Interactions and wearable active devices, these actuators are considered much safe due to their light weight when compared to their commercial counterparts. However their usage are limited, due to their inherent nonlinearities, which poses challenges in their accurate force and position control. The article focuses on dynamic characterization of an in-house fabricated PAM using a three-element lumped phenomenological model. The model consists of a spring element, contractile force element and a damper element arranged in parallel. Pressure perturbation experiments have been conducted to identify the parameters in the governing equations for the spring coefficient, damping coefficient and the contractile element force. Finally, the developed model has been validated by reasonably predicting the displacement response of the PAM to a triangular pressure input pulse when subjected to a constant load on a dynamic test rig. © 2021 IEEE.

关键词： Human robot interaction

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Disturbance Rejection for Pedaling Rehabilitation Robot Based on Integration of Equivalent-Input-Disturbance and Repetitive Control Methods 32

Disturbance Rejection for Pedaling Rehabilitation Robot Base...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Zhou, Yujian She, Jinhua Wang, Feng Iwasaki, Makoto School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Tokyo University of Technology School of Engineering Tokyo Hachioji192-0982 Japan Nagoya Institute of Technology Department of Electrical and Mechanical Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350399714

This study integrated an improved equivalent-input-disturbance (EID) and a repetitive control methods to ensure reference tracking and enhance disturbance-rejection performance for a pedaling rehabilitation robot. A repetitive controller ensures steady-state tracking of a periodic reference input. An EID estimator with a state observer estimates and compensates for the effect of disturbances generated by patients with lower-limb impairment. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show the effectiveness of this method. © 2023 IEEE.

关键词： Disturbance rejection

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A Fuzzy Logic Controller for a Photovoltaic System Relying on a Closed-Loop DC-DC Converter

A Fuzzy Logic Controller for a Photovoltaic System Relying o...

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International Conference on Science Technology engineering and Management (ICONSTEM)

作者： B. Chandrashekar Jayarama Pradeep Muthukumaran. M M. Sivasubramanian K. Lakshmi Khandan Joshuva Arockia Dhanraj Department of Computer Science Engineering St Martin's Engineering College Hyderabad Telangana India Department of Electrical and Electronics Engineering St. Joseph's College of Engineering Chennai Tamil Nadu India Department of Electrical and Electronics Engineering Karpagam college of Engineering Coimbatore Tamil Nadu Department of Electrical and Electronics Engineering Srivenkateswara College of Engineering and Technology Thiruvallur Tamil Nadu India Department of Electrical and Electronics Engineering Madanapalle Institute of Technology and Science Madanapalle Andhra Pradesh India Department of Mechatronics Engineering Centre for Automation and Robotics (ANRO) Hindustan Institute of Technology and Science Chennai Tamil Nadu India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

A DC-DC converter that can handle a lot of different power changes. The experts in this study discovered that adding a fuzzy logic circuit helped the system work better. It makes a big difference in how well and consistently the PV system works that the FLC controls the output power of the converter. Because the FLC works with Microsoft Excel, more people can use this powerful tool for less money and with less trouble. The FLC cuts down on “overshoot,” “settling time,” and steady-state error, as shown in simulations that test how well the controller works. This study may have made it easier for people to start making “fuzzy logic controllers” and make them better. This will have a big effect on how far we get in making energy systems that work better and are more stable. Further investigation could be conducted to determine whether or not these concepts are feasible and how they would enhance the FLC in different types. These DC-DC converters have closed loops in their circuitry.

关键词： Fuzzy logic Photovoltaic systems DC-DC power converters Control systems Energy efficiency Steady-state Spreadsheet programs

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