2022 China Automation Congress (CAC)最新文献_第9页

Research on Phase Shift Full Bridge Converter Based on Nonsingular Terminal Sliding Mode Technology 基于非奇异终端滑模技术的移相全桥变换器研究

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055342

Zhili Xing, Guangxu Zhou, Lei Guo, Ningran Song, Guodong Zhang, Hongwei Zhang

引用次数: 0

Distributed Optimal Output Synchronization of Heterogeneous Multi-agent System with Input Delays 输入时滞异构多智能体系统的分布式最优输出同步

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055216

Yongkang Chen, Huaipin Zhang, Wei Zhao

引用次数: 0

A multi-neighborhood search algorithm for orthogonal packing of identical rectangular items within arbitrary convex regions 任意凸区域内相同矩形物品正交填充的多邻域搜索算法

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10056080

Zhaoyang Wang, Xiangjing Lai, Jun Chu

{"title":"A multi-neighborhood search algorithm for orthogonal packing of identical rectangular items within arbitrary convex regions","authors":"Zhaoyang Wang, Xiangjing Lai, Jun Chu","doi":"10.1109/CAC57257.2022.10056080","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10056080","url":null,"abstract":"In this paper, we propose an efficient heuristic algorithm named the multi-neighborhood search (MNS) algorithm for the problem of packing orthogonally identical rectangles within random convex regions, which is a global optimization problem with many important applications. The problem involves the discrete and continuous optimizations and is shown to be NP-hard. To deal with the discrete and continuous aspects of problem, the proposed global optimization algorithm integrates two neighborhood search methods and the limited-memory BFGS method. Moreover, the algorithm employs a Metropolis acceptance criterion to accept a neighborhood solution as the current solution. The performance of proposed algorithm is assessed on a number of benchmark instances widely used in the literature. Computational results show that the proposed algorithm is quite efficient compared with the existing algorithms in the literature. Particularly, the proposed MNS algorithm is able to find the best known solution for all the tested instances and the computational time is short compared to those of existing algorithms.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132858451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Defect detection for PV Modules based on the improved YOLOv5s 基于改进YOLOv5s的光伏组件缺陷检测

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055183

Shuwei Xu, Huimin Qian, Wenyu Shen, Fangzheng Wang, Xiquan Liu, Zhangjin Xu

{"title":"Defect detection for PV Modules based on the improved YOLOv5s","authors":"Shuwei Xu, Huimin Qian, Wenyu Shen, Fangzheng Wang, Xiquan Liu, Zhangjin Xu","doi":"10.1109/CAC57257.2022.10055183","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10055183","url":null,"abstract":"Cracks and fragments are common defects of photovoltaic (PV) modules, both of which can lead to severe degradation of PV power generation. Traditional fault diagnosis methods are difficult to accurately locate the defect regions in PV modules. In this paper, a developed YOLOv5s is proposed to achieve cracks and fragments detection of PV modules in the electroluminescent (EL) images. More Specific, a defect image dataset is constructed based on image preprocessing and data augmentation on 402 EL images. And a novel cross stage partial operation unit named C3_cbam and a novel spatial pyramidal pooling operation unit named SPP_eca are proposed respectively by combining with visual attention mechanism. Among which, C3_cbam is presented to develop C3_1 unit in YOLOv5s to help the network focus on critical regions in the image by incorporating spatial and channel information. SPP_eca is the improvement of SPP unit by enhancing channel attention to reduce the aliasing effects. The experiment results illustrate that the proposed algorithm achieves 0.923 mAP on the constructed defect image dataset, which has an accuracy increment of 3.3% compared with the original YOLOv5s algorithm. The algorithm also performs well compared to other state-of-art defect detection algorithms.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"712 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133016718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Semantic Segmentation of Ground- Based Cloud Image Based on Fully Convolutional Network 基于全卷积网络的地面云图语义分割研究

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055648

Ji-fei Sun, Ke-bin Jia

{"title":"Research on Semantic Segmentation of Ground- Based Cloud Image Based on Fully Convolutional Network","authors":"Ji-fei Sun, Ke-bin Jia","doi":"10.1109/CAC57257.2022.10055648","DOIUrl":"https://doi.org/10.1109/CAC57257.2022.10055648","url":null,"abstract":"The production, dissipation, and variation of cloud play important roles in the weather forecast such as rain, snow and hail, which are typically reflected in changes in cloud types and cloud cover. It is critical to obtain the cloud cover of each type of cloud quickly and accurately in the constantly changing ground-based cloud images in order to capture and predict weather changes, and the prerequisite is to implement automatic ground-based cloud image segmentation technology classified by cloud type. To implement this technique, this paper introduces a full convolutional network structure in deep learning to implement a segmentation algorithm for ground- based cloud images at the semantic level. We first create the ground-based cloud image database for semantic segmentation (GBCSS). This database includes ten categories of cloud and one category of background for a total of eleven categories, with pixel-level labels for each image. Then, using convolutional neural network structures, we design five full convolutional networks and evaluate the semantic segmentation effects on GBCSS. The experimental results show that all five full convolutional networks have good segmentation accuracy of on GBCSS, with the highest accuracy reaching 75.7%, laying the foundation for the application of semantic segmentation in ground-based cloud image.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133080811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Direct instantaneous current control of Switched Reluctance Motor Based on finite element simulation 基于有限元仿真的开关磁阻电机直接瞬时电流控制

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/cac57257.2022.10055171

Hongyang Li, Guangxu Zhou, Yongyun Mu, Zhili Xing, Qingping Zhang, Xuewei Wang

{"title":"Direct instantaneous current control of Switched Reluctance Motor Based on finite element simulation","authors":"Hongyang Li, Guangxu Zhou, Yongyun Mu, Zhili Xing, Qingping Zhang, Xuewei Wang","doi":"10.1109/cac57257.2022.10055171","DOIUrl":"https://doi.org/10.1109/cac57257.2022.10055171","url":null,"abstract":"Switched reluctance motor (SRM) often adopts current chopping control (CCC) mode during startup and low-speed operation. The traditional CCC has good controllability. However, due to the nonlinear factors of the motor, the actual current cannot track the reference current in real time and there is a large torque ripple will occur in the commutation section of the motor at low-speed mode. Taking three-phase 6/4 SRM as an example, this paper presents a direct instantaneous current control of Switched Reluctance Motor based on finite element simulation. The current torque model is established through finite element simulation to realize the nonlinear mapping from torque to current, and the obtained current value is used to compensate the phase reference current; the total reference current is given by the speed loop and the reference current of each phase is obtained by combining the distribution function. After compared with the actual current, the error enters the fuzzy current chopper controller to optimize the current waveform and make the torque output stable. Finally, compared with the traditional CCC method, the simulation results show that the method is effective.","PeriodicalId":287137,"journal":{"name":"2022 China Automation Congress (CAC)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133505468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Online Stackelberg learning solution for non-zero-sum games with infinite horizon cost* 具有无限视界代价的非零和博弈的在线Stackelberg学习解*

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10056029

Zonglei Jing, Xiaoqian Li, Xianglong Li, P. Ju, Tongxing Li, Shufen Zhao

引用次数: 0

On-orbit Service Mission Planning for Satellites Based on Improved Differential Evolution Algorithm 基于改进差分进化算法的卫星在轨服务任务规划

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055698

Yongbin Yu, Bin Song, Weikui Liang, Guangfu Ma, Yanning Guo

引用次数: 0

Building Fire Simulation Analysis Based on Pyrosim and Revit 基于Pyrosim和Revit的建筑火灾仿真分析

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/cac57257.2022.10054854

Wenpeng Dong, Yulin Cai, Jinfeng Chen

引用次数: 0

Voltage control strategy of high-penetration photovoltaic distribution network based on cluster division 基于集群划分的高渗透光伏配电网电压控制策略

2022 China Automation Congress (CAC) Pub Date : 2022-11-25 DOI: 10.1109/CAC57257.2022.10055653

Na Wu, Yaqian Huang, Shuxian Fan, Guoliang Zhang

引用次数: 0