2021 33rd Chinese Control and Decision Conference (CCDC)最新文献_第8页

Research on Benefit Distribution of E-commerce Rice Sales Supply Chain Based on Cooperative Game 基于合作博弈的电子商务大米销售供应链利益分配研究

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9601616

X. Bai

引用次数: 1

Backstepping Control of a Multimegawatt Variable-speed Wind Turbine for Maximum Power Point Tracking 多兆瓦变转速风力发电机组最大功率点跟踪的反演控制

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9601886

Jingjing Li, Lihui Cen, Yuqian Guo, Yongfang Xie, Fang Liu

{"title":"Backstepping Control of a Multimegawatt Variable-speed Wind Turbine for Maximum Power Point Tracking","authors":"Jingjing Li, Lihui Cen, Yuqian Guo, Yongfang Xie, Fang Liu","doi":"10.1109/CCDC52312.2021.9601886","DOIUrl":"https://doi.org/10.1109/CCDC52312.2021.9601886","url":null,"abstract":"Since the dynamic nonlinear characteristics and the strong inertia of the multimegawatt variable-speed wind turbine(MVWT), the conventional method on maximum power point tracking (MPPT) causes a large wind speed tracking deviation and significant power losses. Due to the ability of fast response, a backstepping control applied to MVWT is proposed. A new nonlinear dynamic model in a lower triangular form is constructed by transforming the complex system into multiple subsystems. The virtual control of each subsystem is selected from top to down of the lower triangular model. And the virtual control laws are obtained based on Lyapunov stability criterion. Until the augmentations recover the last subsystem, the control law of the last subsystem also is the actual control law. Simulation is implemented by using a FAST(Fatigue, Aerodynamic, Structure, and Turbulence) simulator based on the NREL(Nation Renewable Energy Laboratory) offshore 5-MW baseline wind turbine. The results demonstrate that the backstepping control in this paper can improve the tracking performance of rotor speed and increase the power efficiency. The asymptotic stability of the wind turbine system is also guaranteed under circumstance of uncertainties.","PeriodicalId":143976,"journal":{"name":"2021 33rd Chinese Control and Decision Conference (CCDC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127667588","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

The positioning system use for autonomous navigation of unmanned aerial vehicles 该定位系统用于无人机的自主导航

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9602371

Qi Zhang, Yaoxing Wei, Xiao Li, Hanchen Xu

引用次数: 0

Guaranteed-performance leader-following consensus for one-sided Lipschitz nonlinear multi-agent systems 单侧Lipschitz非线性多智能体系统的保证性能领导-跟随共识

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9601566

Wanzhen Quan, Xiaogang Yang, Xinzhong Han, Jianxiang Xi

引用次数: 0

A classification based on random forest for partial discharge sources 局部放电源的随机森林分类

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9602056

Senlin Pu, Huajun Zhang, Cuimin Mao, Guang Yang

引用次数: 0

Aluminum Strip Crown Prediction in Hot Rolling Process Based on Data-driven Methods 基于数据驱动方法的热轧铝带凸度预测

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9601747

Minghao Yao, Shixin Liu, Zhonghua Cao, Shen Yan, Dali Chen

{"title":"Aluminum Strip Crown Prediction in Hot Rolling Process Based on Data-driven Methods","authors":"Minghao Yao, Shixin Liu, Zhonghua Cao, Shen Yan, Dali Chen","doi":"10.1109/CCDC52312.2021.9601747","DOIUrl":"https://doi.org/10.1109/CCDC52312.2021.9601747","url":null,"abstract":"Aluminum process parameters and crown are two important factors that determine the product performance in hot rolling process of aluminum strip. In this paper, we propose a data-driven model fitting method for the relationship between process parameters and crown of aluminum strip hot rolling process. The method includes two parts: the data preprocessing and the relational model fitting. In data preprocessing, we use feature selection algorithm, outlier handling algorithm and missing value padding algorithm to preprocess the given data and obtain high-quality data for analysis. In the relationship model fitting, we use six typical machine learning methods to fit the relationship model between process parameters and crown. Based on the relationship model, we can accurately predict the crown by given process parameters. In order to verify the effectiveness of the proposed algorithm, we construct the dataset of aluminum strip hot rolling process. A large number of experimental results show that this proposed method can be used to build an accurate relationship model between process parameters and crown, and realize the automatic prediction of crown.","PeriodicalId":143976,"journal":{"name":"2021 33rd Chinese Control and Decision Conference (CCDC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126467054","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

A multi-level classification method for fault diagnosis of grid-connected inverter 用于并网逆变器故障诊断的多级分类方法

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9601680

Guangfeng Jin, Junchao Geng, Yue Yu, Tianzhen Wang

引用次数: 0

Adaptive Dynamic Output Feedback Based Cooperative Tracking for Heterogeneous Multi-agent Systems 基于自适应动态输出反馈的异构多智能体系统协同跟踪

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9601846

Kun Liu, Yu-lian Jiang, Zhiyi Wang, Chang Liu, Dongyan Xue

引用次数: 0

Calibration of thermal sensors using BP neural network and SVM 基于BP神经网络和支持向量机的热传感器标定

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9602045

Wenqing Xie, Le Yin, Maojiao Ye

引用次数: 0

An Improved Face Liveness Detection Algorithm Based on Deep Convolution Neural Network 一种改进的基于深度卷积神经网络的人脸活力检测算法

2021 33rd Chinese Control and Decision Conference (CCDC) Pub Date : 2021-05-22 DOI: 10.1109/CCDC52312.2021.9601431

Yan Zhou, Xie Wei, Jinhu Wei

{"title":"An Improved Face Liveness Detection Algorithm Based on Deep Convolution Neural Network","authors":"Yan Zhou, Xie Wei, Jinhu Wei","doi":"10.1109/CCDC52312.2021.9601431","DOIUrl":"https://doi.org/10.1109/CCDC52312.2021.9601431","url":null,"abstract":"Face recognition system has been frequently used in people's daily life. Therefore, face anti-spoofing technology on video and photo has attracted more and more attention. Based on the traditional VGG-11 model, we proposes an improved deep convolution neural network which can accurately detect the face liveness of single face image. Firstly, the training data set is enhanced by some methods such as random rotation, random brightness and saturation adjustment, which can improve the generalization ability of the network. Secondly, batch normalization and random deactivation are added into the traditional VGG-11 network, which can improve feature extraction and decision-making classification of real and false face images. Finally, we use the exponential attenuation learning rate during the process of network training which can avoid the optimization parameters wandering around the local optimization values. Experimental results against the state-of-the-art methods on NUAA and CASIA face liveness databases show that, the proposed method can achieve higher accuracy and lower recognition error rate on face liveness detection.","PeriodicalId":143976,"journal":{"name":"2021 33rd Chinese Control and Decision Conference (CCDC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125984810","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: 2