检索结果-内蒙古大学图书馆

7th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2020

作者： Fan, Zhipeng Sun, Yaping Su, Housheng Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Wuhan China

ISBN: (纸本)9781728162461

The thesis studies the semi-global scaled edge-consensus of linear discrete-time multi-agent systems under both the directed networks and undirected networks, where the states of each edge are subject to input saturation and positive constraint. By virtue of the MARE-based low-gain feedback method, two control protocols about directed networks and undirected networks are devised respectively to promise the positive scaled edge-consensus with input saturation. Thus we find the sufficient conditions to promise the positive edge states and overcome the input saturation. Finally, two representative examples are presented to prove the results. © 2020 IEEE.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Short-Term Residential Load Forecasting Via Pooling-Ensemble Model with Smoothing Clustering

SSRN

引用

SSRN 2023年

作者： Fang, Hongliang Xiao, Jiang-Wen Wang, Yan-Wu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Short-term residential load forecasting is essential to demand side response. However, the frequent spikes in the load and the volatile daily load patterns make it difficult to accurately forecast the load. To deal with these problems, this paper proposes a smoothing clustering method for daily load clustering and a pooling-ensemble model for one day ahead load forecasting. The whole shortterm load forecasting framework in this paper contains three steps. Specifically and firstly, the states of the residents are obtained by clustering the daily load curves with the proposed smoothing clustering method. Secondly, a weighted mixed Markov model is built to predict the probability distribution of the load state in the next day. Thirdly, multiple predictors in the pooling-ensemble model are selected for different states and the load is forecasted by weighing the results of the multiple predictors based on the predicted states. Results of the case studies and comparison studies on two public datasets verify the advantages of the smoothing clustering method and the pooling-ensemble model. © 2023, The Authors. All rights reserved.

关键词： Probability distributions

来源：评论

学校读者我要写书评

暂无评论

Exploiting Learnable Joint Groups for Hand Pose Estimation 35

Exploiting Learnable Joint Groups for Hand Pose Estimation

引用

35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence

作者： Li, Moran Gao, Yuan Sang, Nong Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan Peoples R China Tencent AI Lab Shenzhen Peoples R China

ISBN: (纸本)9781577358664

In this paper, we propose to estimate 3D hand pose by recovering the 3D coordinates of joints in a group-wise manner, where less-related joints are automatically categorized into different groups and exhibit different features. This is different from the previous methods where all the joints are considered holistically and share the same feature. The benefits of our method are illustrated by the principle of multi-task learning (MTL), i.e., by separating less-related joints into different groups (as different tasks), our method learns different features for each of them, therefore efficiently avoids the negative transfer (among less related tasks/groups of joints). The key of our method is a novel binary selector that automatically selects related joints into the same group. We implement such a selector with binary values stochastically sampled from a Concrete distribution, which is constructed using Gumbel softmax on trainable parameters. This enables us to preserve the differentiable property of the whole network. We further exploit features from those less-related groups by carrying out an additional feature fusing scheme among them, to learn more discriminative features. This is realized by implementing multiple 1x1 convolutions on the concatenated features, where each joint group contains a unique 1x1 convolution for feature fusion. The detailed ablation analysis and the extensive experiments on several benchmark datasets demonstrate the promising performance of the proposed method over the state-of-the-art (SOTA) methods. Besides, our method achieves top-1 among all the methods that do not exploit the dense 3D shape labels on the most recently released FreiHAND competition at the submission date. The source code and models are available at https://***/ moranli-aca/LearnableGroups-Hand.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Joint Load Prediction of Multiple Buildings Using Multi-Task Learning with Selected-Shared-Private Mechanism

SSRN

引用

SSRN 2023年

作者： Cao, Minghui Xiao, Jiang-Wen Fang, Hongliang Li, Yuan-Zheng Wang, Yan-Wu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Wuhan430074 China

Short-term load forecasting for residential buildings is of great significance to ensure the safe and economic operation of power grid. However, most of the existing prediction methods focus on the temporal characteristics of individual buildings and ignore the importance of spatial characteristics between different buildings. To tackle this problem and realize joint prediction for multiple buildings, a novel multi-task learning model with the selected-shared-private mechanism is proposed in this paper. Firstly, the temporal and spatial characteristics hidden in electricity consumption patterns are analyzed and represented by auto-correlation and cross-correlation, respectively. Then, a correlation-oriented combination strategy considering the auto-correlation and time dependency is proposed to build input set for the prediction model, and the temporal convolutional network is adopted to extract features. Furthermore, this paper designs a novel selected-shared-private mechanism based on the cross-correlation, which can selectively utilize information from related tasks while focusing on private features to improve prediction accuracy. The proposed model is compared with other methods on the public dataset, and the results demonstrate the superiority of this model in load prediction for multiple buildings. © 2023, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Restart strategy for sensorless PMSM drive system based on zero-voltage vector

引用

IET ELECTRIC POWER APPLICATIONS 2020年第12期14卷 2362-2369页

作者： Chen, Bao Shen, Anwen Li, Peihe Luo, Xin Xu, Sang Xu, Jinbang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan Peoples R China

The zero-voltage vector (ZVV) method is widely employed to restart a free-running permanent magnet synchronous machine (PMSM) stably in a sensorless drive system due to its simple implementation. However, in the conventional method, it is hard to determine the action time and interval time of ZVV pulses, which may result in overcurrent. Moreover, the estimation accuracy is susceptible to current measurement noise. To cope with these problems, an enhanced ZVV method based on two feedback loops is proposed. With the proposed strategy, an inner closed loop is constructed to regulate the action time of the ZVV pulse by keeping the current amplitude at the reference value, which prevents the overcurrent. Meanwhile, the reference value of the current amplitude is adjusted automatically based on the outer loop to determine a suitable interval time of the ZVV pulse. Furthermore, the phase-locked loop technique is exploited to extract rotor speed and position. The feasibility of the proposed method is verified under simulation and experimental results with a 5.5 kW sensorless PMSM drive system.

关键词： rotors permanent magnet motors phase locked loops closed loop systems feedback synchronous motor drives sensorless machine control noise measurement ZVV feedback loops inner closed loop ZVV pulse phase-locked loop sensorless PMSM drive system restart strategy zero-voltage vector permanent magnet synchronous machine sensorless drive system

来源：评论

学校读者我要写书评

暂无评论

control-oriented dynamic process optimization of solid oxide electrolysis cell system with the gas characteristic regarding oxygen electrode delamination

引用

APPLIED ENERGY 2023年第1期332卷

作者： Xia, Zhiping Zhao, Dongqi Li, Yuanzheng Deng, Zhonghua Kupecki, Jakub Fu, Xiaowei Li, Xi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Mini Wuhan 430074 Hubei Peoples R China Shenzhen Huazhong Univ Sci Technol Res Inst Shenzhen 518055 Guangdong Peoples R China Huazhong Univ Sci & Technol Belt & Rd Joint Lab Measurement & Control Technol Wuhan 430074 Hubei Peoples R China Inst Power Engn Ctr Hydrogen Technol CTH2 Augustowka 36 PL-02981 Warsaw Poland Inst Power Engn Mory 8 PL-01330 Warsaw Poland Univ Calif Irvine Natl Fuel Cell Res Ctr NFCRC Engn Lab Facil Irvine CA 92697 USA

Fast response, strong reliability, and high efficiency as the critical objectives of a solid oxide electrolysis cell (SOEC) system, which requires the system to operate under optimal operating conditions and switching manners. Therefore, various research has been carried out on its characteristic security. Most of them focus on the thermal characteristics security without further considering the security of gas characteristics regarding oxygen electrode delamination. However, this is one of the most critical degradations of SOEC. Herein, a novel SOEC system dynamic model with the gas characteristic regarding oxygen electrode delamination is proposed for the first time to optimize operation. Specially, the advantages are discussed through the optimization analysis of both the secure operation range regarding certain operating conditions and the steady-state operating points of the sys-tem. Subsequently, the dynamic process constraints of oxygen electrode delamination, fuel starvation, and power fast tracking during dynamic switching are investigated. The feasibilities of multi-step, parabola, and ramp schemes in solving the problems above are also evaluated. The outcomes show that the ramp scheme is preferred. Furthermore, the priority issue between oxygen electrode delamination and fuel starvation is studied, and cor-responding dynamic process optimization strategies are developed for high and low initial power with a two-step switching method. After that, the dynamic process optimizations of two representative cases are investigated in detail. The optimization results show that the system efficiency is increased, and the safe ramp duration under the low initial power is significantly shortened. The findings of this study could provide a basis for developing control strategies for SOEC systems with fluctuating energy input.

关键词： Solid oxide electrolysis cell (SOEC) Dynamic response Security constraints Optimization scheme System efficiency

来源：评论

学校读者我要写书评

暂无评论

A data-driven digital-twin model and control of high temperature proton exchange membrane electrolyzer cells

引用

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2022年第14期47卷 8687-8699页

作者： Zhao, Dongqi He, Qijiao Yu, Jie Guo, Meiting Fu, Jun Li, Xi Ni, Meng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist Wuhan Hubei Peoples R China Hong Kong Polytech Univ Dept Bldg & Real Estate Res Inst Sustainable Urban Dev RISUD Res Inst Smart Energy RISEHung HomKowloon Hong Kong Peoples R China

The high temperature proton exchange membrane electrolyzer cells (HT-PEMEC) are promising for hydrogen generation from fluctuating and intermittent renewable energy. In this study, a data-driven method is developed to study the dynamic behavior of HT-PEMEC. This method combines multiphysics simulation and nonlinear system identification, avoiding expensive experimental costs and time-consuming full multiphysics calculations. Dynamic models for predicting the power consumption, hydrogen production and temperature are identified, and the verified fit is 96.31%, 97.87%, 87.73%, respectively, which demonstrated the accuracy of the identification model. Subsequently, the identification model was used to predict the dynamic behavior of HT-PEMEC and design control strategies. Fuzzy control strategy and neural network predictive control strategy are implemented to alleviate overshoot and suppress fluctuations so as to improve the durability of the electrolyzer. Moreover, compared with the fuzzy control strategy, the neural network predictive control strategy reduces the power overshoot by approximately 92%. This data drive digital-twin model can not only guide dynamic experimental research, but also can be extended to study the dynamic behavior of various fuel cells and electrolyzer cells. (c) 2021 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Proton exchange membrane electrolyzer cell Data-driven method Numerical modeling Dynamic research control strategy

来源：评论

学校读者我要写书评

暂无评论

control-oriented performance prediction of solid oxide electrolysis cell and durability improvement through retard oxygen electrode delamination with reverse operation

引用

ENERGY CONVERSION AND MANAGEMENT 2023年第1期277卷

作者： Xia, Zhiping Zhao, Dongqi Zhou, Yihuan Deng, Zhonghua Kupecki, Jakub Fu, Xiaowei Li, Xi Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist Wuhan 430074 Hubei Peoples R China Shenzhen Huazhong Univ Sci & Technol Res Inst Shenzhen 518055 Guangdong Peoples R China Huazhong Univ Sci & Technol Belt & Rd Joint Lab Measurement & Control Technol Wuhan 430074 Hubei Peoples R China Inst Power Engn Ctr Hydrogen Technol CTH 2 Augustowka 36 PL-02981 Warsaw Poland Inst Power Engn Mory 8 PL-01330 Warsaw Poland Univ Calif Irvine Natl Fuel Cell Res Ctr NFCRC Engn Lab Facil Irvine CA 92697 USA

Oxygen electrode delamination is the key degradation mechanism of reversible solid oxide cells (rSOC) operating in the electrolysis mode. Previous experimental studies have shown that rSOC operating in fuel cell mode can mitigate this degradation and extend its lifetime. As a result, this paper proposes a multiscale degradation model that integrates microscale structures, mesoscale parameters, and macroscale performances to investigate the sensitivity of the alleviation of oxygen electrode delamination to reverse operating conditions. After that, the model is validated by available experimental data at the microscale and macroscale. Subsequently, the multiscale degradation behaviors regarding certain operating conditions are discussed. The analysis demonstrates that, on the one hand, the cell degradation is mainly attributed to lanthanum zirconate oxide (LZO) formation during long-term operation;on the other hand, the higher the temperature and current density, the faster the degra-dation. Consequently, a new parameter of LZO layer thickness related to oxygen electrode delamination is introduced to assess the sensitivities of durability improvement to reverse operating variables, namely starting switch moment, operating duration, and operating temperature. Meanwhile, voltage degradation rate and hydrogen production are also evaluated. The result indicates that a decrease in the starting switch moment and an increase in the operating duration can reduce the growth of LZO layer thickness and prolong the incubation time for oxygen electrode delamination. It can also decrease the degradation rate and hydrogen production. However, improving reverse operating temperature reduces the LZO layer thickness growth rate and degradation rate without affecting hydrogen production.

关键词： Reversible solid oxide cell Degradation modeling Evaluation criteria Reverse operation Sensitivity analysis

来源：评论

学校读者我要写书评

暂无评论

Semiglobal Observer-Based Positive Scaled Edge-Consensus of Networked Discrete-Time Systems Under Actuator Saturation

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2021年第7期51卷 4543-4554页

作者： Sun, Yaping Su, Housheng Wang, Xiaoling Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China Nanjing Univ Posts & Telecommun Coll Automat Nanjing 210023 Peoples R China

In this article, by using the linear graph theory, modified algebraic Riccati equation (MARE)-based method and duality principle, two interaction protocols are proposed to achieve the scaled edge-consensus of networked discrete-time systems with unmeasurable edge-sates. Meanwhile, drawing support from MARE-based low-gain feedback technique and positive system theory, sufficient conditions are derived to ensure the bounded control inputs and positive edge-states. Moreover, feedback matrices and observer matrices are, respectively, constructed by utilizing the solutions of MARE and modified algebraic dual Riccati equation (MADRE). Remarkably, the theoretical results only use the edge number and vertex number of network rather than the global information of network. Finally, five examples are shown to demonstrate the feasibility of the interaction protocols.

关键词： Protocols Observers Actuators Discrete-time systems Sun Riccati equations image edge detection Actuator saturation discrete-time low-gain feedback observer positive constraint scaled edge consensus

来源：评论

学校读者我要写书评

暂无评论

Generation Maintenance Scheduling for Power Systems Considering the Risk Quantification of Hybrid Uncertainty

引用

IEEE Transactions on Power Systems 2025年

作者： Yang, Xiao Zhao, Yong Li, Yuanzheng Huang, Cheng Ding, Qiang Key Laboratory of Image Information Processing and Intelligent Control of Ministry of Education of China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China Power Science Research Institute of State Grid Jiangsu Electric Power Company China China Electric Power Research Institute Company China

The accurate quantification of risk caused by uncertainty forms a crucial foundation for formulating the generation maintenance scheduling (GMS) of power systems. However, the probability distribution functions (PDFs) of uncertain variables such as wind power and load are challenging to model accurately or are unknown, which makes it difficult to measure their economic risk and formulate appropriate GMS for power systems. To address this issue, we consider hybrid uncertainty from wind power and load, and propose a novel interval-probabilistic worst conditional value-at-risk (IP-WCVaR)-based generation maintenance scheduling method. Firstly, a novel IP-WCVaR method is proposed to measure the risk of the interval and probabilistic hybrid uncertainty, and the analytical mathematical model of the IP-WCVaR is derived through typical scenarios of probability correction. On this basis, the positive and negative spinning reserve models are established using the IP-WCVaR and then integrated into the GMS model, which enhances the resilience of the power system. Finally, the new risk-averse GMS model is formulated as the lower and upper boundary optimal models, which are transformed into tractable mixed integer linear programming problems based on the interval extreme value theory. The effectiveness and superiority of the proposed IP-WCVaR method are verified on the modified IEEE 24-bus and IEEE 118-bus power systems. © 1969-2012 IEEE.

关键词： Mixed-integer linear programming

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：