检索结果-内蒙古大学图书馆

5th International Conference on Power and Energy Technology, ICPET 2023

作者： Chen, Kaiwen Wang, Qingyi Kang, Kai Wang, Hao School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China PowerChina Hubei Electric Engineering Co. Ltd Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

ISBN: (纸本)9798350339673

Based on the background of photovoltaic development in the whole county and the demand for energy storage on the user-side, this paper establishes an economic evaluation model of user-side photovoltaic energy storage system considering shared energy storage. Firstly, three schemes of no energy storage, independent energy storage and shared energy storage are proposed, and the influence of photovoltaic energy storage system loss on annual power generation is considered. Secondly, based on the whole life cycle theory, the cost and benefit model of the user-side photovoltaic energy storage system is established, and the unit electricity cost of the user is used as the evaluation index. Finally, the relevant data of user in Hubei area are analyzed as an example to verify the effectiveness of the model and provide reference for the investment of related projects. © 2023 IEEE.

关键词： photovoltaic energy storage system shared energy storage the unit electricity cost of the user user-side

来源：评论

学校读者我要写书评

暂无评论

Meta-State-Space Learning: An Identification Approach for Stochastic Dynamical systems

arXiv

引用

arXiv 2023年

作者： Beintema, Gerben I. Schoukens, Maarten Toth, Roland Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

Available methods for identification of stochastic dynamical systems from input-output data generally impose restricting structural assumptions on either the noise structure in the data-generating system or the possible state probability distributions. In this paper, we introduce a novel identification method of such systems, which results in a dynamical model that is able to produce the time-varying output distribution accurately without taking restrictive assumptions on the data-generating process. The method is formulated by first deriving a novel and exact representation of a wide class of nonlinear stochastic systems in a so-called meta-state-space form, where the meta-state can be interpreted as a parameter vector of a state probability function space parameterization. As the resulting representation of the meta-state dynamics is deterministic, we can capture the stochastic system based on a deterministic model, which is highly attractive for identification. The meta-state-space representation often involves unknown and heavily nonlinear functions, hence, we propose an artificial neural network (ANN)-based identification method capable of efficiently learning nonlinear meta-state-space models. We demonstrate that the proposed identification method can obtain models with a log-likelihood close to the theoretical limit even for highly nonlinear, highly stochastic systems. © 2023, CC BY.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

On Improved Commutation for Moving-Magnet Planar Actuators

arXiv

引用

arXiv 2023年

作者： Broens, Yorick Butler, Hans Tóth, Roland The Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands ASML Veldhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Hungary

The demand for high-precision and high-throughput motion control systems has increased significantly in recent years. The use of moving-magnet planar actuators (MMPAs) is gaining popularity due to their advantageous characteristics, such as complete environmental decoupling and reduction of stage mass. Nonetheless, model-based commutation techniques for MMPAs are compromised by misalignment between the mover and coil array and mismatch between the ideal electromagnetic model and the physical system, often leading to decreased system performance. To address this issue, a novel improved commutation approach is proposed in this paper, which is applicable for general planar motor applications, by means of dynamic regulation of the position dependence of the ideal model-based commutation algorithm, which allows for attenuation of magnetic misalignment, manufacturing inaccuracies and other unmodelled phenomena. The effectiveness of the proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator *** Codes 37M15 © 2023, CC BY.

关键词： Alignment

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Gear Shift Schedule Design for 2-AMT Electric Vehicles Based on Sparrow Search Algorithm

Comprehensive Gear Shift Schedule Design for 2-AMT Electric ...

引用

Chinese control Conference (CCC)

作者： Tianyi Wang Liling Ma Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing P.R. China

With the aim of 2-AMT electric vehicles, a comprehensive shift schedule that considers both power and economy is proposed. First, the objective function of the comprehensive shift schedule is constructed, which is the weighted sum of vehicle acceleration time and vehicle power consumption per unit distance. Second, Sparrow Search Algorithm is used to solve the objective function and obtain the comprehensive shift schedule. Finally, AVL Cruise simulation software is used to simulate vehicle dynamics and economy under an NEDC. The results show that the comprehensive shift schedule is similar to the optimal power shift schedule in terms of dynamic performance, and the economy is optimized by 3%. The feasibility of the comprehensive shift schedule is verified.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Development of a Method for Generating Extremely High Reference Motion Speeds of Mechatronic Objects Moving Alone or in a Group

Development of a Method for Generating Extremely High Refere...

引用

International Russian Smart Industry Conference (SmartIndustryCon)

作者： Anton Gubankov Igor Gornostaev Robotics Laboratory Institute of Automation and Control Processes FEB RAS Laboratory of Marine Unmanned Aviation and Marine Aviation Systems Admiral G.I. Nevelskoy Maritime State University Vladivostok Russia Laboratory of Robotic Systems M.D. Ageev Institute of Marine Technology Problems FEB RAS

The paper presents the results of developing a method for generating reference control signals that describe the desired law of movement of various mechatronic objects (unmanned aerial vehicles, mobile land and underwater robots, etc.) along smooth trajectories specified by parametric splines. In order to maintain high dynamic accuracy of control of these mechatronic objects, including when solving group control problems, it is proposed to adjust their reference movement speed, taking into account the specified restrictions on the developed accelerations. Taking into account these restrictions is necessary to reduce the reference speed in sections of the trajectory with increased curvature. To implement the proposed approach, a method was developed and a system was synthesized, the performance of which was confirmed by the results of numerical simulation. The presented system is designed to operate in conditions where the reference trajectory of a mechatronic object is unknown in advance and is formed (or adjusted) directly during the mission without the possibility of preliminary calculations. Also, this system does not require complex calculations and can be implemented on the basis of low-power on-board computers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Exploring the use of deep learning in task-flexible ILC*

Exploring the use of deep learning in task-flexible ILC*

引用

American control Conference (ACC)

作者： Anantha Sai Hariharan Vinjarapu Yorick Broens Hans Butler Roland Tóth Department of Electrical Engineering Eindhoven University of Technology Eindhoven The Netherlands ASML Veldhoven The Netherlands Systems and Control Laboratory Institute for Computer Science and Control Hungary

Growing demands in today’s industry results in increasingly stringent performance and throughput specifications. For accurate positioning of high-precision motion systems, feedforward control plays a crucial role. Nonetheless, conventional model-based feedforward approaches are no longer sufficient to satisfy the challenging performance requirements. An attractive method for systems with repetitive motion tasks is iterative learning control (ILC) due to its superior performance. However, for systems with non-repetitive motion tasks, ILC is generally not applicable, despite of some recent promising advances. In this paper, we aim to explore the use of deep learning to address the task flexibility constraint of ILC. For this purpose, a novel Task Analogy based Imitation Learning (TAIL)-ILC approach is developed. To benchmark the performance of the proposed approach, a simulation study is presented which compares the TAIL-ILC to classical model-based feedforward strategies and existing learning-based approaches, such as neural network based feedforward learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Robust Dynamic Latent Variable Model for Dynamic Process Monitoring With Missing Data in Cyber-Physical systems

IEEE Transactions on Industrial Cyber-Physical Systems

引用

IEEE Transactions on Industrial Cyber-Physical systems 2023年 1卷 227-235页

作者： Le Zhou Lixinqian Yu Beiping Hou Hongbo Zheng Zheng-Guang Wu School of Automation and Electrical Engineering Zhejiang University of Science & Technology Hangzhou China Faculty of Engineering and IT University of Melbourne Melbourne Australia National Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Although remarkable studies on dynamic process modeling and monitoring in cyber-physical systems have been conducted, there are still several limitations to these approaches, rendering them unsuitable for practical applications. Firstly, the common dynamic models are built based on complete data, which means that their modeling performance usually deteriorates when there are missing measurements. Secondly, practical data often exhibits more complex characteristics, such as non-stationary and non-Gaussian noises. Therefore, a robust dynamic latent variable model is proposed to address the challenges of dynamic process modeling and monitoring in complex measurement environments with missing values. The proposed method effectively handles non-Gaussian noises and recursively estimates missing values, thus enhancing the monitoring performance within the dynamic latent variable modeling framework. Finally, the feasibility and superiority of the proposed method are evaluated through a numerical example and a real wastewater treatment case, demonstrating its effectiveness and practicality in real-world scenarios.

关键词： Cyber-physical systems Principal component analysis Process monitoring Data models Load modeling Numerical models Loading

来源：评论

学校读者我要写书评

暂无评论

City-wide Solar Radiation Potential Analysis by Coupling Physical Modelling and Machine Learning

City-wide Solar Radiation Potential Analysis by Coupling Phy...

引用

2024 Symposium on Spatial Information to Empower the Metaverse

作者： Chen, Xiana Yu, Junxian Tu, Wei Chen, Long Guangdong Key Laboratory of Urban Informatics Shenzhen University Guangdong Shenzhen518060 China Ministry of Natural Resources Key Laboratory for Geo-Environmental Monitoring of Great Bay Area Shenzhen University Guangdong Shenzhen518060 China Shenzhen Key Laboratory of Spatial Smart Sensing and Services Guangdong Shenzhen518060 China School of Architecture and Urban Planning Shenzhen University Guangdong Shenzhen518060 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Addressing the challenges posed by climate change and meeting urban energy demands is of utmost importance in today's world. Building Integrated Photovoltaics (BIPV) emerges as a crucial solution for energy conservation and carbon emissions reduction in urban environments. However, traditional methods of assessing solar radiation on buildings using physical models are often computationally intensive and time-consuming. This paper introduces a novel hybrid approach that integrates physical model-based solar radiation calculation with machine learning techniques to analyze Solar Radiation Potential (SRP) across city-wide building infrastructure. The proposed approach precisely evaluates the SRP of representative blocks by leveraging computing-intensive physical models integrated with 3D building data. Subsequently, two machine learning models are developed to effectively predict the SRP of building roofs and facades across the entire city. To validate the efficacy of this approach, an experiment was conducted in Shenzhen, China, yielding insightful results. The findings reveal that Shenzhen has a huge potential for BIPV solar power generation, with mean annual total building roof and facade solar radiation values of 9.22 * 107kwℎ and 2.47 * 108kwℎ, respectively. It can be further observed that relying solely on rooftop installations is insufficient to meet electricity demand. This study not only provides an innovative alternative for city-wide SRP estimation by combining physical modeling and machine learning but also offers valuable insights for fostering low-carbon urban environments and informing data-driven and model-driven urban planning and management strategies. © Author(s) 2024.

关键词： Solar power generation

来源：评论

学校读者我要写书评

暂无评论

Complex Fusion Structure Slow Dissociation Simulation Prediction Method

Complex Fusion Structure Slow Dissociation Simulation Predic...

引用

2024 China automation Congress, CAC 2024

作者： Zhang, Dongsheng Wang, Yigeng Huang, Wanyi Naval Architecture & Ocean Engineering Institute China Shipbuilding NDRI Engineering Co.Ltd Shanghai200090 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China School and Hospital of Stomatology China Medical University Shenyang110016 China Liaoning Provincial Key Laboratory of Oral Diseases China Medical University Shenyang110016 China

ISBN: (纸本)9798350368604

Human skeletal implants, as a category of critically important medical consumables, are designed to remain inside the body for long periods. Titanium or titanium alloys are commonly chosen as the primary construction materials. Recently, the academic community has explored an innovative approach to implant construction that uses titanium as the base framework and zinc as the filling material to create an interconnected composite structure. In this structure, zinc gradually dissolves over the lifetime of the implant, promoting bone growth into the pores formed after its dissolution. Given the continuous dissociation of zinc, the physical and chemical properties of the implant exhibit a slow and continuous change over its lifecycle. However, there is currently no effective method to precisely predict and assess the state changes of such complex structures over long periods of *** study focuses on the typical application scenarios of human skeletal implants, and verifies the accuracy of short-term steady-state numerical calculation models through rigorous experimental methods. Based on this, we propose a complex fusion structure slow dissociation reverse simulation prediction method based on short-term steady-state calculation results. This method aims to simulate the steady-state performance of implants in the short term, and reverse deduce the structural changes and performance evolution caused by zinc dissociation during long-term use, thereby providing a more scientific basis and support for the design and evaluation of medical implants. © 2024 IEEE.

关键词： Titanium alloys

来源：评论

学校读者我要写书评

暂无评论

Autonomous Crowdsensing: Operating and Organizing Crowdsensing for Sensing automation

arXiv

引用

arXiv 2024年

作者： Wu, Wansen Yang, Weiyi Li, Juanjuan Zhao, Yong Zhu, Zhengqiu Chen, Bin Qiu, Sihang Peng, Yong Wang, Fei-Yue College of Systems Engineering National University of Defense Technology Hunan Province Changsha410073 China Hunan Institute of Advanced Technology Hunan Province Changsha410073 China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

—The precise characterization and modeling of Cyber-Physical-Social systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sensing capabilities. To address this issue, Crowdsensing Intelligence (CSI) has been proposed to collect data from CPSS by harnessing the collective intelligence of a diverse workforce. Our first and second Distributed/Decentralized Hybrid Workshop on Crowdsensing Intelligence (DHW-CSI) have focused on principles and high-level processes of organizing and operating CSI, as well as the participants, methods, and stages involved in CSI. This letter reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by a range of technologies such as decentralized autonomous organizations and operations, large language models, and human-oriented operating systems. Specifically, we explain what ACS is and explore its distinctive features in comparison to traditional crowdsensing. Moreover, we present the "6A-goal" of ACS and propose potential avenues for future research. Copyright © 2024, The Authors. All rights reserved.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：