检索结果-内蒙古大学图书馆

International Conference on Smart Energy Systems and Technologies (SEST)

作者： Maria Fotopoulou George Tsekouras Dimitrios Rakopoulos Vassiliki Kontargyri Department of Electrical and Electronics Engineering University of West Attica Athens Greece Chemical Process and Energy Resources Institute Centre for Research and Technology Hellas Athens Greece Control Systems and Industrial Automation Laboratory National and Kapodistrian University of Athens Athens Greece

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

Following the latest energy market trends, active distribution systems incorporate an ascending mix of flexible loads, which can participate in Demand Response (DR) strategies. The purpose of this research paper is to present a DR strategy for the Distribution System Operator (DSO) in order to enhance the system's operation and mitigate power quality issues, such as voltage drops, and congestion. The proposed algorithm aims at smoothing the load curve, taking into consideration the available flexible load and the limitations of the system. The algorithm is demonstrated on a model of the distribution system of Skiathos island, Greece, in the context of ENFLATE, a Horizon Europe project, and future scenarios with photovoltaic (PV) penetration are studied as well. According to the results, the proposed DR algorithm manages to reduce the voltage drop, eliminate the number of events where the voltage drop exceeds the limits and reduce the losses of the distribution system up to 8%-9%, depending on the PV penetration.

关键词： Electric potential Smoothing methods Power quality Europe Voltage Artificial neural networks Transformers Demand response Load modeling Context modeling

来源：评论

学校读者我要写书评

暂无评论

Robust Mass Flow control in Hot Rolling Mills

Robust Mass Flow Control in Hot Rolling Mills

引用

Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ulrich Knechtelsdorfer Andreas Steinboeck Andreas Kugi Christian Doppler Laboratory for Model-Based Process Control in the Steel Industry Automation and Control Institute TU Wien Wien Automation and Control Institute TU Wien Wien

ISBN: (纸本)9781728164021

In tandem finishing mills, the roll speed of the mill stands is synchronized to ensure a uniform mass flow at each mill stand. This simplifies the control of the strip exit thickness at each mill stand and the inter-stand strip tension. Existing state-of-the-art synchronization control concepts do not consider the time-variant behavior of the slip between the strip and the work rolls. This behavior can be considered by adaptive control laws but they rely on measurements of the inter-stand strip speeds. However, sensor faults cannot be completely precluded. Therefore, a robust roll speed synchronization control law that can cope with sensor faults is derived in this paper. A method to detect and isolate faults of the inter-stand strip speed measurement is introduced. In case of a detected fault, the control law is switched to a form which does not require the respective measurement. Stability of the overall closed loop system is proven by Lyapunov’s indirect method and its efficacy is demonstrated by simulations using a validated plant model.

关键词： Strips Industry applications Switches Stability analysis Synchronization Velocity measurement Adaptive control

来源：评论

学校读者我要写书评

暂无评论

Nonlinear industrial process fault diagnosis with latent label consistency and sparse Gaussian feature learning

引用

Journal of Central South University 2022年第12期29卷 3956-3973页

作者： LI Xian-ling ZHANG Jian-feng ZHAO Chun-hui DING Jin-liang SUN You-xian Science and Technology on Thermal Energy and Power Laboratory Wuhan 2nd Ship Design and Research InstituteWuhan 430205China State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhou 310027China State Key Laboratory of Synthetical Automation for Process Industries(Northeastern University) Shenyang 110819China

With the increasing complexity of industrial processes, the high-dimensional industrial data exhibit a strong nonlinearity, bringing considerable challenges to the fault diagnosis of industrial processes. To efficiently extract deep meaningful features that are crucial for fault diagnosis, a sparse Gaussian feature extractor(SGFE) is designed to learn a nonlinear mapping that projects the raw data into the feature space with the fault label dimension. The feature space is described by the one-hot encoding of the fault category label as an orthogonal basis. In this way, the deep sparse Gaussian features related to fault categories can be gradually learned from the raw data by SGFE. In the feature space,the sparse Gaussian(SG) loss function is designed to constrain the distribution of features to multiple sparse multivariate Gaussian distributions. The sparse Gaussian features are linearly separable in the feature space, which is conducive to improving the accuracy of the downstream fault classification task. The feasibility and practical utility of the proposed SGFE are verified by the handwritten digits MNIST benchmark and Tennessee-Eastman(TE) benchmark process,respectively.

关键词： nonlinear fault diagnosis multiple multivariate Gaussian distributions sparse Gaussian feature learning Gaussian feature extractor

来源：评论

学校读者我要写书评

暂无评论

Enhanced Soft Sensor with Qualified Augmented Data Using Centroid Measurement Criterion

Enhanced Soft Sensor with Qualified Augmented Data Using Cen...

引用

2021 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2021

作者： Dai, Yun Yu, Qing Yang, Tao Yao, Yuan Liu, Yi Zhejiang University of Technology Institute of Process Equipment and Control Engineering Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

ISBN: (纸本)9781665402453

Development of reliable soft sensors using limited labeled samples is not an easy task in industrial processes. A selective generative adversarial network (SGAN)-based support vector regression (SGAN-SVR) soft sensor is proposed for quality prediction using limited labeled training data. Specifically, SVR is considered as a base prediction model. The Wasserstein GAN (WGAN) is adopted to capture the distribution of available labeled data and generate virtual candidates. Subsequently, using a proposed similarity measurement strategy, those synthetic data with more information are selected and introduced into the training set. Using the designed data augmentation approach, the SGAN-SVR model can achieve better prediction performance compared with the SVR soft sensor. The quality prediction results on an industrial polyethylene process demonstrate the effectiveness and advantages of the proposed method. © 2021 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Augmented Yield Analysis for Refined Elementary Mode Set of Penicillin Metabolic Network

Augmented Yield Analysis for Refined Elementary Mode Set of ...

引用

第33届中国过程控制会议

作者： Chenxi Tao Quan Li Zhonggai Zhao Fei Liu School of Internet of Things Engineering Jiangnan University Key Laboratory of Advanced Control of Light Industry Process (Ministry of Education) Institute of AutomationJiangnan University

Penicillin is usually produced by microbial growth and metabolism in a fermentation *** analysis and understanding of metabolic behavior are the keys to improving penicillin *** refined elementary model set(REMS) is a subset of the Elementary Models(EMs) necessary to describe specific metabolic *** plays an important role in mechanistic modeling and optimization of penicillin fermentation *** conventional yield analysis(YA) method can easily derive REMS using yield information,but the metabolic behavior described by the results may seriously deviate from *** this paper,we propose an augmented yield analysis(AYA) method to address this ***,basic metabolic pathways and metabolites characterizing their activities are identified;second,the production fluxes of the identified metabolites are combined with yield information to form an augmented yield space,into which the EMS is recoded;finally,the REMS is formed by a minimal set of EMs which can meet the preset requirements for metabolic *** REMS of the penicillin metabolic network is determined by AYA,and it can describe the actual metabolic behavior of penicillin,thereby verifying the effectiveness of AYA.

关键词： Penicillin metabolic network elementary mode analysis refined elementary mode set metabolic information augmented yield analysis

来源：评论

学校读者我要写书评

暂无评论

Deep Graph Network for process Soft Sensor Development

Deep Graph Network for Process Soft Sensor Development

引用

2021 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2021

作者： Jia, Mingwei Dai, Yun Xu, Danya Yang, Tao Yao, Yuan Liu, Yi Zhejiang University of Technology Institute of Process Equipment and Control Engineering Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

ISBN: (纸本)9781665402453

In the (bio)chemical processes, traditional hardware sensors are difficult to directly measure the quality of critical products due to their time-varying, non-linear, and dynamic characteristics. This makes process soft sensor modeling methods important. Since the process variables can be regarded as natural graph data, this work introduces graphs in the soft sensor modeling area. A soft sensor model based on the graph neural network (GNN) is proposed. The model can learn the topological structure of graph data between each unit variable. Moreover, it characterizes variable relationships from the spatial and temporal dimensions to the output prediction by introducing the spatial-temporal convolutional layer. The effectiveness and advantages of the GNN-based soft sensor model are verified using a simulated fermentation process. © 2021 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Observer-Based Distributed Sensor Fault-Tolerant Model Predictive control for Intermittent Faults ⁎

引用

IFAC-PapersOnLine 2021年第3期54卷 251-256页

作者： Guannan Xiao Xiaoli Luan Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

For distributed control systems with intermittent sensor faults, a distributed fault and state combined observer is designed, and an observer switching mode strategy is proposed to improve the observer convergence performance, then a distributed fault-tolerant model predictive is designed based on the observer. In the proposed observer, the distributed system observer matrices, and state and fault estimation are computed in a totally distributed way with some transition matrices, which can consider the coupled states. The switching mode observer can be more targeted. The two modes: state only estimation, both state and fault estimation are switched due to the absence or presence of the sensor faults. The approach is shown effective through a simulated example.

关键词： Model predictive control distributed control fault-tolerant control fault estimation distributed observer

来源：评论

学校读者我要写书评

暂无评论

Optimization-based estimator for the lateral strip position in tandem hot rolling ⁎

引用

IFAC-PapersOnLine 2021年第11期54卷 7-12页

作者： Florian Schausberger Christopher Pietschnig Andreas Ettl Andreas Steinboeck Andreas Kugi voestalpine Stahl GmbH Linz Austria Christian Doppler Laboratory for Model-Based Process Control in the Steel Industry Automation and Control Institute (ACIN) TU Wien Vienna Austria Automation and Control Institute (ACIN) TU Wien Vienna Austria

This paper deals with the estimation of the lateral motion of steel strips during the hot strip rolling process in a tandem finishing mill. The method presented in this paper uses an image sequence captured by a 2D-CMOS camera. In the considered application, just a small segment of the strip is inside the camera field of view and thus an image sequence has to be used for online estimation. An optimization-based algorithm uses the image data and the knowledge about the constraints of the strip movement in the rolling gap for robust estimation of the lateral position and width of the strip. Measurement data from a tandem finishing mill show the performance of the designed algorithm.

关键词： Measurement of lateral strip position Hot strip rolling mill Unconstrained optimization Moving horizon estimation Model-based estimator Snaking

来源：评论

学校读者我要写书评

暂无评论

Semi-Supervised process Data Regression and Application Based on Latent Factor Analysis Model

引用

IEEE Transactions on Instrumentation and Measurement 2023年 72卷 1页

作者： Zheng, Junhua Liu, Yangxuan Liu, Yi Hou, Beiping Yao, Yuan Zhou, Le Zhejiang University of Science and Technology School of Automation and Electrical Engineering Hangzhou310023 China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

This article investigates the problem of modeling regression with labeled and unlabeled data samples commonly found in industrial processes. By incorporating additional information on unlabeled data samples, a new semi-supervised latent factor analysis model is developed. Compared with the purely supervised regression models which can only use the information of labeled dataset, the semi-supervised model can efficiently extract useful information for improvement of the regression performance. Furthermore, the proposed basic semi-supervised model has been extended to a mixture form, which is capable of describing data from more complex processes. For predictive modeling for key/mass variables, two soft sensors are constructed based on the semi-supervised models. Then, three case studies are used to evaluate the performance of the proposed soft sensing methods. © 2023 IEEE.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

Eco-driving of fuel cell electric trucks: optimal speed planning combining dynamic programming and Pontryagin’s minimum principle

Eco-driving of fuel cell electric trucks: optimal speed plan...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Alessandro Ferrara Christoph Hametner Division of Process Control and Automation TU Wien Institute of Mechanics and Mechatronics Vienna Austria Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria

ISBN: (纸本)9781665454698

Eco-driving is an energy-aware driving style that improves the overall vehicle efficiency to reduce operating costs and extend the driving range. This paper focuses on the eco-driving of fuel cell electric trucks, optimizing the speed plan based on the route elevation, and studying the trade-off between driving time and range. In particular, the optimal speed plan is created by combining two methods from optimal control theory (dynamic programming and Pontryagin’s minimum principle) to include an energy management strategy for fuel consumption optimization. The speed plan created with the proposed method increases the vehicle range by 8% compared with a constant speed plan. Moreover, the study shows that the vehicle range can be extended up to 50% if the driving time is increased, which might be an essential solution to cope with the undeveloped hydrogen refueling infrastructure. The conclusion of this work indicates several directions to continue the research on the topic: for example, addressing robustness to traffic conditions and including component degradation mitigation targets in the optimization (e.g. SoC operating range and fuel cell voltage degradation).

关键词： Degradation Vehicular and wireless technologies Hydrogen Fuel cells Voltage Robustness Planning

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：