2019 Chinese Control And Decision Conference (CCDC)最新文献_第8页

A Second-order Grey Model for Forecasting Interval Number Series 区间数序列预测的二阶灰色模型

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8832866

Zeng Xiangyan, HE Fang-li, S. Yanchao, Yan Shuli

引用次数: 0

Random trajectory tracking of flexible manipulator with buffer 带缓冲的柔性机械臂随机轨迹跟踪

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8833033

Hongwei Li, Zhaojing Wu, Dianfeng Zhang

引用次数: 1

Research of Improved Sphere Decoding Algorithm 改进球面解码算法的研究

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8833103

Xiao Jun, Guan Diyuan, Wang Zengye

引用次数: 1

Lateral Dynamic Modeling and Verification of Vehicles with Steering Characteristics 具有转向特性的车辆横向动力学建模与验证

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8832806

Bo Xie, Yanbo Zhao, Yantao Tian, Guangming Nie

{"title":"Lateral Dynamic Modeling and Verification of Vehicles with Steering Characteristics","authors":"Bo Xie, Yanbo Zhao, Yantao Tian, Guangming Nie","doi":"10.1109/CCDC.2019.8832806","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832806","url":null,"abstract":"This paper proposed the vehicle lateral dynamic modeling method including the characteristics of the steering system. The model can demonstrate the aligning torque and some other characteristics. For the steering system, the input is made up of the driver's torque, the assisting motor torque and the aligning torque obtained from the tire model, the corresponding output is the front wheel angle. The vehicle status information includes the sideslip angle, the yaw rate and the lateral displacement, and the aligning torque can be characterized. The steering system includes the influence of the steering system clearance, elastic components, the overall stiffness, and the ability to express the road feeling. The tire model includes the expression of different road surfaces, the influence of the steering system on the lateral stiffness characteristics, and the influence of the front wheel positioning parameters on the tire cornering characteristics. The lateral dynamic model is mainly used for simulation research and system performance evaluation. Then, the expression ability of the model is verified by the joint simulation of CarSim and Simulink. Finally, the experiment of a snake test was designed. It appears that the integrated model lays a foundation of the designing a controller in the future.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124422326","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

Post Evaluation System of Nuclear Power Plant Construction Based on Comprehensive Fuzzy Theory 基于综合模糊理论的核电厂建设后评价体系

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8833059

Li Xie, Yujie Sun

引用次数: 1

Short-term Wind Speed Prediction Based on CNN_GRU Model 基于CNN_GRU模型的短期风速预测

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8833472

Huai Nana, Dong Lei, W. Lijie, Hao Ying, Zhongjian Dai, Wang Bo

{"title":"Short-term Wind Speed Prediction Based on CNN_GRU Model","authors":"Huai Nana, Dong Lei, W. Lijie, Hao Ying, Zhongjian Dai, Wang Bo","doi":"10.1109/CCDC.2019.8833472","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833472","url":null,"abstract":"This paper proposes a new combined prediction model for short-term wind speed prediction. The article uses Numerical Weather Prediction (NWP) and actual wind speed as input to the CNN_GRU model. The normalization method is used to solve the problem of the difference in magnitude between different data types. In order to extract the data characteristics between wind direction, temperature, air pressure, numerical weather forecast wind speed and actual wind speed, a continuous data matrix is constructed. The processed data set is divided into training set and test set. First, the characteristics of the data set are extracted using a Convolutional Neural Network (CNN). The fully connected layer then processes the extracted features and inputs them to the GRU network. Finally, the final predicted wind speed is obtained through the output layer. In order to avoid the gradient dispersion caused by the Sigmoid, this paper uses the Relu as the activation function of the network. The CNN_GRU model is compared with the CNN model and the continuous method under the same conditions. The results show that the proposed CNN_GRU model has the best effect in short-term wind speed prediction.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116684740","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: 10

CSR: A Centrality Based on Robustness and Controllable Subspace of Complex Networks 基于鲁棒性和可控子空间的复杂网络中心性

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8833288

A. Mahmood, Umair Usman, Lin Wang

{"title":"CSR: A Centrality Based on Robustness and Controllable Subspace of Complex Networks","authors":"A. Mahmood, Umair Usman, Lin Wang","doi":"10.1109/CCDC.2019.8833288","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833288","url":null,"abstract":"Complex networks are everywhere, some of them are airline network, road network, power grid network and protein-to-protein network. These networks are robust in failure or under attack but still needs in-depth study. Researchers have proposed various techniques to find and enhance the robustness of networks. However, furthers study required in this area. In this paper, we study the robustness of controllable subspace under random removal of edges and propose the robustness index for controllable subspace from one node as well as from a set of nodes. This work proposes a new centrality CSR (Controllable Subspace and robustness) to rank the important nodes of network based on optimal values of controllable subspace and robustness of controllable subspace. We also discuss the effects of exact robustness index and approximate robustness index on two factor: computational time, and accuracy. We show the analysis of top ten percent important nodes of various real networks with different centrality measures and CSR to compare the results. With the extensive experimentation on the real networks, CSR outperformed other centrality measures.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116882315","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 of energy consumption information collection based on object-oriented technology 基于面向对象技术的能耗信息采集研究

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8832867

Hongli Liu, Junjie Lv, Lei Shao, Ji Li

引用次数: 0

Active disturbance rejection time-varying formation control for multi-agent systems with disturbances 具有扰动的多智能体系统的自抗扰时变群体控制

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8833166

Le Wang, Hui Yao, Cheng Wang, Jianxiang Xi, Guangbin Liu

引用次数: 0

Crack Damage Detection of Bridge Based on Convolutional Neural Networks 基于卷积神经网络的桥梁裂纹损伤检测

2019 Chinese Control And Decision Conference (CCDC) Pub Date : 2019-06-01 DOI: 10.1109/CCDC.2019.8833336

xiaoyu Jia, W. Luo

引用次数: 2