2022 4th International Conference on Control and Robotics (ICCR)最新文献_第8页

The Influence Analysis of the Power Grid Topology on the Stray Current Invading Transformers 电网拓扑结构对杂散电流侵入变压器的影响分析

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053889

He Zhong, Jiangtao Liu, Mingwei Tang, Jianlei Zhang, Kai Liu, Song Xiao, Yujun Guo

{"title":"The Influence Analysis of the Power Grid Topology on the Stray Current Invading Transformers","authors":"He Zhong, Jiangtao Liu, Mingwei Tang, Jianlei Zhang, Kai Liu, Song Xiao, Yujun Guo","doi":"10.1109/ICCR55715.2022.10053889","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053889","url":null,"abstract":"During the operational process of the metro lines, the traction current discharged from the working grounding wheels flows back to the terrestrial traction substations through the steel rail, as the DC stray current may be generated due to the poor insulating condition between the rail and the ground. The characteristics of the DC stray current invading the transformer settled at the terrestrial substation is affected by a series elements including the train's operational condition, the ‘rail -ground’ transition resistance, the soil structure and power grid topology. Exploring the influence factors of the stray current lays the foundations for further preventing the negative impact brought from stray current. In order to analyze the influence of the power grid topology on the stray current invading transformers, a coupling model involving the up and down metro lines with the power grid is built, based on the finite element method (FEM). Based on this FEM model, the variation of stray current invading the transformer is analyzed along with the relative position between the power grid single circuit and the metro line varying, meanwhile the variation of the power grid's topology is also considered. It is found that with the complexity of the power grid topology, the total amount of stray current invading the power grid increases, whereas the stray current flowing through the majority of the transmission lines decreases. In addition, no matter the two transformers constituting the power grid circuit are on the same side or on the opposite side of the metro line, the stray current invading the grid tends to increase with the reduction of the angle between the metro line and the power grid circuit.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126735410","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

Application of Small Animals Control in Substation Based on GBDT and LR Fusion Algorithm 基于GBDT和LR融合算法的变电站小动物控制应用

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053897

Zhaofeng Chen

引用次数: 0

Stochastic Linear Quadratic Game for Discrete-time Systems Based-on Adaptive Dynamic Programming 基于自适应动态规划的离散系统随机线性二次对策

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053887

Shibo Na, Ruizhuo Song

引用次数: 0

Mobile Humanoid Robot Control through Object Movement Imagery 基于物体运动图像的移动人形机器人控制

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053905

Eneo Petoku, G. Capi

{"title":"Mobile Humanoid Robot Control through Object Movement Imagery","authors":"Eneo Petoku, G. Capi","doi":"10.1109/ICCR55715.2022.10053905","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053905","url":null,"abstract":"Brain-Computer Interface research aims to build systems that can connect the brain to computer or a certain robotic application. The brain activity is solely used to generate commands that can be recognized by the computer. To generate a recognizable brain activity, usually the subject imagines the movements of one's limbs without performing any real movement. In the literature, this paradigm is called Motor Imagery (MI). The subject provides data through a particular recording technology, such as EEG, in a certain time frame, in which the subject forces himself/herself into the feeling of performing a particular action. Each recorded data is linked to a label, and different techniques are used to learn patterns, in order to map them correctly. The goal of this paper is to investigate, whether it is possible to generate similar results as in the case of imagining the movement of limbs, by imagining the movement of an external object. To investigate this, we compare the performance of Motor Imagery and Object Motor Imagery. In the first case the mental task consists of imagining the movements of arms, while in the second the imagining of moving an external box through solely brain activity. A video of a box that moves through a plane in two directions, right, left, is used as visual feedback in both cases. The recorded EEG data are split into training and testing subsets, and are fed to a deep neural network, that tries to learn the different patterns and to classify them. The results show that Object Motor Imagery can achieve better results compared to MI, despite the lack of embodiment and congruity with any daily neural command. The trained architecture is used to control a mobile humanoid, investigating the implementation of Object Motor Movement in robotic application.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"7 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114011899","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

Robot Dynamic Path Planning Based on Improved A* and DWA Algorithms 基于改进A*和DWA算法的机器人动态路径规划

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053929

Chenxi Guan, Shuying Wang

引用次数: 6

Communication and Control Co-design for Networked Control Systems under DoS Attacks and Time-varying Delays DoS攻击和时变时延下网络控制系统的通信与控制协同设计

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053879

Lulu Zhou, Chen Peng, Z. Cao

引用次数: 0

Convolutional Neural Network Based Unmanned Ground Vehicle Control via Deep Reinforcement Learning 基于深度强化学习的卷积神经网络无人地面车辆控制

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053931

Yongxin Liu, Qiang He, Junhui Wang, Zhiliang Wang, Tianheng Chen, Shichen Jin, Chi Zhang, Zhiqiang Wang

引用次数: 1

Node Deployment and Energy Saving Optimization Method for Wireless Sensor Networks Based on Q-learning 基于q -学习的无线传感器网络节点部署及节能优化方法

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053885

Shujun Huang, Zhihua Zhang, Ruofeng Xie

引用次数: 0

Off-policy Q-learning-based Tracking Control for Stochastic Linear Discrete-Time Systems 基于离策略q学习的随机线性离散系统跟踪控制

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053863

X. Liu, Lei Zhang, Yunjian Peng

引用次数: 0

Comparisons of RCM Generation Algorithms for Vision-Controlled Robotic Endoscope 视觉控制机器人内窥镜RCM生成算法的比较

2022 4th International Conference on Control and Robotics (ICCR) Pub Date : 2022-12-02 DOI: 10.1109/ICCR55715.2022.10053894

Weibing Li, Biao Song, Yongping Pan

{"title":"Comparisons of RCM Generation Algorithms for Vision-Controlled Robotic Endoscope","authors":"Weibing Li, Biao Song, Yongping Pan","doi":"10.1109/ICCR55715.2022.10053894","DOIUrl":"https://doi.org/10.1109/ICCR55715.2022.10053894","url":null,"abstract":"In minimally invasive surgery (MIS), a surgical endoscope is an essential instrument that provides visualization for the surgeon. One principal characteristic of surgical instruments is that remote center of motion (RCM) must be respected. To meet such a practical requirement, many physical RCM mechanisms and software-based RCM generation algorithms have been proposed. As compared with physical RCM mechanisms, RCM generation algorithms possess more flexibility due to the fact that the RCM point can be adjusted if required. This paper conducts comparisons of four typical RCM generation algorithms applied to a vision-controlled robotic endoscope under joint constraints. Kinematic models of the robotic endoscope and the four RCM generation algorithms are first briefly introduced. Then, a unified control formulation based on quadratic programming (QP) is constructed to incorporate kinematic, RCM, and physical constraints of the robotic endoscope. Based on the unified control scheme, comparative simulations and experiments are performed. The advantages and disadvantages of the four typical RCM generation algorithms are analyzed and discussed. When performing a same peg transfer task in the simulations, the RCM errors synthesized by RCM generation algorithms designed using a plane equation and an insertion equation are smaller. In the physical experiments, there are few differences in the RCM errors. Nevertheless, it is revealed that the joint velocities corresponding to the RCM generation algorithm based on a plane equation are the smallest, which means that the joint angles change more gently and it can be more friendly to MIS.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131787790","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