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9th International Conference on Fluid Power and Mechatronics, FPM 2023

作者： Dong, Yuemei Chen, Chen Shi, Jian School of Automation Science and Electrical Engineering Beihang University Beijing China Shen Yang Aircraft Design and Research Institute AVIC Department of Mechatronics Systems Shenyang China

ISBN: (纸本)9798350304947

When the aircraft lands, the nose landing gear is subjected to impact loading, which can cause fatigue damage and affect its reliability. In this paper, finite element method and fatigue life prediction techniques are used to analyze the fatigue mechanism and reliability of the nose landing gear. Firstly, the dynamic and kinematic models of the key components of the retractable mechanism of the nose landing gear were established. Finite element analysis was carried out using ANSYS to obtain the stress-strain distribution of the mechanism through numerical simulation. Subsequently, on the basis of the stress-strength interference model, the probabilistic method was adopted to establish an accumulated damage-antifatigue damage strength-time dynamic interference model for multiple cyclic stresses. Finally, through analysis of multi-level variable load experimental test data, the fatigue life and reliability assessment of the nose landing gear were obtained. The results indicate that the fatigue life and reliability of the landing gear are severely affected by variable load impact, and this research has practical significance for improving the reliability of aircraft and accident prevention. © 2023 IEEE.

关键词： Finite element method

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Multi-Agent Electricity Energy Substitutions Planning Considering Uncertainty 6

Multi-Agent Electricity Energy Substitutions Planning Consid...

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6th International Conference on HVDC, HVDC 2024

作者： Wang, Linlin Cheng, Xingong Zhang, Sirui Bu, Fanpeng Liu, Weiliang Wang, Luhao School of Automation and Electrical Engineering University of Jinan Jinan China Electricity and Energy Efficiency Institute China Electric Power Research Institute Beijing China State Grid Jiaxing Power Supply Company Department of Development Jiaxing China

ISBN: (纸本)9798350387759

This paper offers solutions to various obstacles in the current landscape of domestic electricity energy substitutions, such as disorderly development, mounting pressure on grid power supply, and conflicting interests among different agents. Firstly, we present a novel approach to address the challenges associated with domestic electricity energy substitutions by introducing a multi-agent distributed cooperative planning model. The model is designed to tackle demand uncertainty while focusing on the planning of electric boilers, electric heat pumps, and electric flue-curing tobacco machines. Secondly, we leverage the Linear Decision Rule (LDR) to handle demand variability during the planning phase. Thirdly, by integrating the planning model with regional distribution networks' power flow dynamics, the Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) algorithm is deployed to optimize both the planning capacity and operational power for electricity energy substitutions. The case analysis confirms the model's effectiveness, demonstrating that electric energy substitution can address user requirements while optimizing economic benefits. © 2024 IEEE.

关键词： demand uncertainty electricity energy substitutions multi-agent planning

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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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A Review on Control Strategies of Grid-connected Energy Storage Systems for Frequency Regulation 5

A Review on Control Strategies of Grid-connected Energy Stor...

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5th International Academic Exchange Conference on Science and Technology Innovation, IAECST 2023

作者： Tian, Yuting Chen, Yang Wei, Wei Xia, Yan State Grid Sichuan Electric Power Research Institute Chengdu China Tsinghua University Department of Electrical Engineering Beijing China Sichuan University of Science & Engineering School of Automation and Information Engineering Yibin China

ISBN: (纸本)9798350357738

With the escalating ratio of renewable energy in the modern power system, the unpredictability and instability of renewable energy significantly impact the electricity reliability of the system. Simultaneously, the extensive integration of power electronic devices has resulted in increased damping and inertia losses within the power system, seriously affecting its frequency stability. Due to its shortcomings, such as long start-up times and slow frequency response, traditional frequency regulation units have been incapable of meeting the frequency regulation needs of new power systems. Therefore, Battery Energy Storage Systems (BESS), with their frequency support capability and fast response rate, have garnered considerable attention for application. The participation of BESS in the auxiliary market has also emerged as a key focus of research. This paper initially presents the grid-connected control strategy of BESS, subsequently analyzing the research status of BESS providing primary and secondary frequency regulation services in power systems, and offering prospects for further research trends. © 2023 IEEE.

关键词： Renewable energy

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Zonotope-based fault estimation for Lipschitz nonlinear systems 3

Zonotope-based fault estimation for Lipschitz nonlinear syst...

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2024 3rd International Conference on Aerospace and Control engineering, ICoACE 2024

作者： Ma, Siyuan Zhang, Wei Jiang, Qiang Gao, Sheng School of Automatic and Electrical Engineering Shenyang Ligong University Shenyang110158 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China China-Portugal Belt and Road Joint Laboratory on Space & Sea Technology Advanced Research Shanghai200120 China

An estimation of fault intervals using a T-N-L structured observer is suggested for Lipschitz nonlinear systems. By augmenting state vectors, the augmentation system and its observer are established, enabling the observer to concurrently estimate fault and system states. The L∞ performance is applied to enhance the resilience of the fault interval estimation to external disturbances and unanticipated inputs. An adequate requirement for the observer design is also presented. The interval estimation of states and faults is ultimately created by using a zonotope. The proposed method exhibits advantages and feasibility when compared to existing simulation techniques. © 2025 institute of Physics Publishing. All rights reserved.

关键词： Nonlinear systems

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Modeling and Robust Control of Single Board Heater System with Arduino based Implementation 2

Modeling and Robust Control of Single Board Heater System wi...

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2nd IEEE International Conference on Intelligent Technologies, CONIT 2022

作者： Miyani, Piyush B. Thakar, Parth S. Markana, Anilkumar Gujarat Power Engineering and Research Institute Electrical Engineering Department Mehsana India Institute for Systems and Robotics Instituto Superior Técnico Lisbon Portugal Pandit Deendayal Energy University Electrical Engineering Department Gandhinagar India

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

In this paper, a new discrete-time implementation of sliding mode control is proposed through open-source Arduino-based hardware for a single board heater system (SBHS). The designed control input with discrete-time sliding mode control (DSMC) is realized by proposing a MOSFET-based current control circuit. This designed hardware will provide a plat-form for researchers and practitioners to validate their control algorithms with ease of use through Arduino-based control implementation. Besides, the proposed strategy also features the first of its kind practical application of DSMC for temperature control using Arduino which is not reported before. The designed control is validated in terms of setpoint tracking for temperature control through the simulation studies in MATLAB and also through hardware implementation with the Arduino controller. The obtained simulation and experimental results showcase the efficacy of the proposed methods. © 2022 IEEE.

关键词： Temperature control

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research Progress on Industrial Robots: A Review

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Recent Patents on Mechanical engineering 2025年

作者： Shinde, Vilas B. Pawar, Padmakar J. Gadakh, Vijay S. Department of Automation & Robotics Engineering Amrutvahini College of Engineering Sangamner Ahmednagar Savitribai Phule Pune University Maharashtra Pune422 608 India Department of Robotics & Automation Engineering K. K. Wagh Institute of Engineering Education and Research Nashik Savitribai Phule Pune University Maharashtra Pune422 003 India

The success of the fourth and upcoming fifth industrial resolution lies majorly in automation and robotics. Industrial robots perform various manufacturing-related tasks due to their autonomy, flexibility, and autonomous work in a complex environment. Applications including drilling, material transfer, loading and unloading machines, processing, assembling, and inspection, welding, spray painting, machining, and so on are common. The present work comprehensively summarizes all the pertinent work related to the industrial robot, such as inverse kinematics problems, robot design, programming, scheduling, motion planning, and trajectory planning. In addition, the present work discusses various optimization algorithms employed in industrial robots. Furthermore, several recommendations for future research have been addressed. © 2024 Bentham Science Publishers.

关键词： Unloading

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An electrical Distance and Data-Driven Partitioning Power Quality Control Strategy for Distribution Networks 19th

An Electrical Distance and Data-Driven Partitioning Power Qu...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Wang, Jing Jing, Hui Liu, Jing Guo, Yue Qiao, Bin Grid Operation Training Department State Grid of China Technology Jinan250001 China State Grid Economic Research Institute Beijing100000 China School of Automation and Electrical Engineering University of Jinan Jinan250001 China

ISBN: (纸本)9789819613786

A partitioning control strategy tailored specifically for distribution networks is introduced in this paper,which is reliant on precise electrical distance calculations and an in-depth grey relational analysis of power quality time series data. The electrical distances between nodes are accurately computed by utilizing the sensitivity method and based on the relationship between reactive power and voltage amplitude at nodes, thus unveiling the strength of electrical connections within the distribution network. The interplay of power quality among various nodes is thoroughly examined through the utilization of time series data pertaining to power quality, in conjunction with grey relational analysis. The integration of these two key indicators facilitates the holistic segmentation of the network, enabling targeted control measures for distinct areas. This strategic approach is aimed at elevating the overall power quality of the entire distribution network. To validate the efficacy of this method, the widely recognized IEEE 14-bus distribution system is employed as the benchmark model. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Power distribution networks

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Fed-NILM: A federated learning-based non-intrusive load monitoring method for privacy-protection

Energy Conversion and Economics

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Energy Conversion and Economics 2022年第2期3卷 51-60页

作者： Wang, Haijin Si, Caomingzhe Liu, Guolong Zhao, Junhua Wen, Fushuan Xue, Yusheng The School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Department of Electrical Engineering Tsinghua University Beijing China Department of Electrical Engineering Zhejiang University Hangzhou China Institute of Artificial Intelligence and Robotics for Society Shenzhen China State Grid Electric Power Research Institute Nanjing China

Non-intrusive load monitoring (NILM) is essential for understanding consumer power consumption patterns and may have wide applications such as in carbon emission reduction and energy conservation. Determining NILM models requires massive load data containing different types of appliances. However, inadequate load data and the risk of power consumer privacy breaches may be encountered by local data owners when determining the NILM model. To address these problems, a novel NILM method based on federated learning (FL) called Fed-NILM is proposed. In Fed-NILM, instead of local load data, local model parameters are shared among multiple data owners. The global NILM model is obtained by averaging the parameters with the appropriate weights. Experiments based on two measured load datasets are performed to explore the generalization capability of Fed-NILM. In addition, a comparison of Fed-NILM with locally trained NILM models and the centrally trained NILM model is conducted. Experimental results show that the Fed-NILM exhibits superior performance in terms of scalability and convergence. Fed-NILM out performs locally trained NILM models operated by local data owners and approaches the centrally trained NILM model, which is trained on the entire load dataset without privacy protection. The proposed Fed-NILM significantly improves the co-modelling capabilities of local data owners while protecting the privacy of power consumers. © 2022 The Authors. Energy Conversion and Economics published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology and the State Grid of China Economic & Technological research institute Co Ltd.

关键词： Data privacy

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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data 49

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Cheng, Haibo He, Yunpeng Zeng, Peng Li, Shichao Vyatkin, Valeriy Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350331820

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction. © 2023 IEEE.

关键词： Forecasting

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