IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society最新文献_第3页

Robust Real-time Junction Detection Under Various Conditions Using Dark Channel Maps 基于暗通道映射的各种条件下鲁棒实时结检测

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9969099

Hyung-Joon Jeon, Jaewook Jeon

{"title":"Robust Real-time Junction Detection Under Various Conditions Using Dark Channel Maps","authors":"Hyung-Joon Jeon, Jaewook Jeon","doi":"10.1109/IECON49645.2022.9969099","DOIUrl":"https://doi.org/10.1109/IECON49645.2022.9969099","url":null,"abstract":"The study in this paper aims to demonstrate the performance of a junction detection architecture based on a deep learning paradigm, included with dark channel transformation. We must take into account the hostile conditions when detecting such features. Many of previous papers proposed models for junction detection with hand-crafted logic, which works well under normal conditions but not under hostile conditions. This necessitates a data-driven approach for junction detection. We attempt to do so using two recently proposed deep neural networks: ResNet50 and EfficientNet-B0. Here, given a set of input images of roads with junctions or no junctions, dark channel transformation is applied to better inform the networks about the road regions prominent in the images. According to our experiments on the Oxford RobotCar Dataset, using the dark channel transformation on the ResNet50 trained from scratch can achieve a junction classification accuracy of over 94%. This numerical figure is 8% greater than when the ResNet50 pre-trained on ImageNet is directly trained on RGB Oxford dataset images. When using pre-trained weights of the deep networks, junction classification accuracy rises to 95%, and the precision increases to 99%.","PeriodicalId":125740,"journal":{"name":"IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115037819","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 Non-Invasive Current Estimator for Integrated Dual-DC Boost Converter Topology 集成双直流升压变换器拓扑的非侵入式电流估计器

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9968527

Kausik Biswas, Ritam Chakraborty, O. Ray

{"title":"A Non-Invasive Current Estimator for Integrated Dual-DC Boost Converter Topology","authors":"Kausik Biswas, Ritam Chakraborty, O. Ray","doi":"10.1109/IECON49645.2022.9968527","DOIUrl":"https://doi.org/10.1109/IECON49645.2022.9968527","url":null,"abstract":"Multi-port dc-dc converter topologies have been reported as potential solutions for different applications, e.g., renewable integration, power sharing, and multi-source applications. This paper evaluates one such multi-port dc-dc converter topology known as integrated dual-dc boost converter (IDDBC), which can be used to interface two different dc sources into a common load. One of the major challenges related to IDDBC operation is the management of power flow between different ports of the topology. Current sensing and measurement are essential for realizing these control objectives. Conventional current sensors (e.g. sense resistors, Hall Sensors) are transducers that are invasive, expensive, and require associated conditioning circuits. This paper proposes a non-invasive digital current estimation technique for IDDBC topology. This approach requires terminal voltage measurements and analog comparators to estimate the inductor currents of the topology. The proposed method of current estimation has been demonstrated using a laboratory prototype of IDDBC using an FPGA-based controller.","PeriodicalId":125740,"journal":{"name":"IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115261139","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

Validation of a Property Estimation Method Based on Sequential and Posteriori Estimation 一种基于序列和后验估计的属性估计方法的验证

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9968845

T. Kitamura, Atsumi Saito, Keisuke Yamazaki, Yuki Saito, H. Asai, K. Ohnishi

引用次数: 0

Cases of Soft Switching in a Series Resonant Balancing Converter for Bipolar DC Grids 双极直流电网串联谐振平衡变换器软开关实例

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9969022

Sachin Yadav, Zian Qin, P. Bauer

引用次数: 0

Adaptive Power Allocation with Real-Time Monitoring and Optimization for Fuel Cell/Supercapacitor Hybrid Energy Storage Systems 基于实时监测和优化的燃料电池/超级电容器混合储能系统自适应功率分配

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9968352

Qiuyu Li, Hengzhao Yang, Qian Xun

{"title":"Adaptive Power Allocation with Real-Time Monitoring and Optimization for Fuel Cell/Supercapacitor Hybrid Energy Storage Systems","authors":"Qiuyu Li, Hengzhao Yang, Qian Xun","doi":"10.1109/IECON49645.2022.9968352","DOIUrl":"https://doi.org/10.1109/IECON49645.2022.9968352","url":null,"abstract":"Electric vehicles powered by hybrid energy storage systems composed of fuel cells and supercapacitors are of great interest. To further improve the efficiency of such hybrid systems, better energy management strategies need to be developed. This paper proposes an adaptive power allocation method with real-time monitoring and optimization for fuel cell/supercapacitor hybrid energy storage systems used in electric vehicles. This method utilizes a low-pass filter to distribute power between fuel cells and supercapacitors. The cut-off frequency of the filter is obtained by splitting the load current spectrum according to the supercapacitor state of charge (SOC). The DC-link voltage fluctuation and the supercapacitor SOC are monitored in a real-time fashion. Consequently, a real-time optimization scheme is developed to reduce the dependence of the proposed algorithm on its initial parameters and enhance the adaptivity of the proposed algorithm. To validate the effectiveness of the proposed method, a Simulink model is developed and two standard drive cycles (i.e., NYCC and US06) are selected. Simulation results show that the DC-link voltage fluctuation drops significantly and the supercapacitor SOC can be effectively controlled.","PeriodicalId":125740,"journal":{"name":"IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122307610","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: 4

Deep Learning with Fractional Order Operaters Lagrangian Method for Space Robot based on Sliding Mode-based Fixed-time Control 基于滑模定时控制的空间机器人分数阶算子深度学习拉格朗日方法

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9968416

Tongyu Zhao, Guanghui Sun, Biqing Qi, Xiangyu Shao, D. Zhou

{"title":"Deep Learning with Fractional Order Operaters Lagrangian Method for Space Robot based on Sliding Mode-based Fixed-time Control","authors":"Tongyu Zhao, Guanghui Sun, Biqing Qi, Xiangyu Shao, D. Zhou","doi":"10.1109/IECON49645.2022.9968416","DOIUrl":"https://doi.org/10.1109/IECON49645.2022.9968416","url":null,"abstract":"Many approaches have been influential in the robotics field because of deep learning (DL). As space robots need more reliability and stability, model-free algorithms with deep learning have particular advantages over the traditional methods in space environment. In this paper, we present an original robot current/torque prediction based on robot dynamic system with deep learning. Also, we add sliding mode-based fixed-time controller to improve the control performance. It has analysed manipulator current information through robot dynamic property’s matrix nature from fewer samples. This method has significant benefits in terms of robot current/torque identification and tracking. It also performs well in robustness and learning rates. This generic method has developed to solve a variety of problems using deep learning and data filtering with manipulator dynamics process, which includes deep learning with fractional order differential operators, robot dynamics and Kalman smoothing. We verified our algorithm into a real two-joint space robot on air-floating platform in zero gravity environment. The final results show it can learn to predict current/torque based on robot dynamics and complete the finitetime convergence. This paper made several key contributions to the fields of current/torque identification and prediction with manipulator dynamics and deep learning in space robot models. It performs very well in robot current/torque tracking and predicting new situations.","PeriodicalId":125740,"journal":{"name":"IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122367532","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

Multi-port Smart Transformer Integration in Residential Buildings 住宅楼宇中的多端口智能变压器集成

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9968955

Fermín Mendoza Azores, E. Romero-Cadaval, Joaquin Carbonell Cuéllar, Javier Rodríguez Barrero

引用次数: 0

Linear Temporal Logic-based Mixed-Integer Linear Problem Planning with the Koopman Operator 基于时间线性逻辑的Koopman算子混合整数线性问题规划

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9969097

Shumpei Tokuda, M. Yamakita, Hiroyuki Oyama, Rin Takano

{"title":"Linear Temporal Logic-based Mixed-Integer Linear Problem Planning with the Koopman Operator","authors":"Shumpei Tokuda, M. Yamakita, Hiroyuki Oyama, Rin Takano","doi":"10.1109/IECON49645.2022.9969097","DOIUrl":"https://doi.org/10.1109/IECON49645.2022.9969097","url":null,"abstract":"We present a formulation for a linear temporal logic (LTL)-based task planning using the Koopman operator. The dynamics of nonlinear systems can be represented as linear systems by lifting them to a space of augmented states using the Koopman operator. On the other hand, the lifted linear system cannot capture the nonlinear effects of inputs, which appear in many robotic systems. Therefore, instead of a lifted linear system, we can consider representing control-affine bilinear systems. However, since the lifted bilinear systems are nonlinear, we need to solve nonlinear programming problems for trajectory optimization. This paper presents a methodology for the trajectory optimization problem of the lifted bilinear system. Using the mixed-integer convex approximation, we can solve the trajectory optimization problem of the lifted bilinear systems as a mixed-integer linear programming problem. This formulation allows us to solve LTL-based task planning problems for nonlinear systems. The effectiveness of the proposed method was confirmed by numerical simulations.","PeriodicalId":125740,"journal":{"name":"IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122898088","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

An MQTT Gateway for HIL Testing of Energy Systems 用于能源系统HIL测试的MQTT网关

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9969054

Diran Liu, Daniele Carta, A. Xhonneux, D. Müller, A. Benigni

引用次数: 0

Control of Cascaded H-bridge Converters for Power Line Communication 电力线通信级联h桥变换器的控制

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society Pub Date : 2022-10-17 DOI: 10.1109/IECON49645.2022.9969079

Ioannis Mandourarakis, E. Koutroulis, G. N. Karystinos

{"title":"Control of Cascaded H-bridge Converters for Power Line Communication","authors":"Ioannis Mandourarakis, E. Koutroulis, G. N. Karystinos","doi":"10.1109/IECON49645.2022.9969079","DOIUrl":"https://doi.org/10.1109/IECON49645.2022.9969079","url":null,"abstract":"Power line communication (PLC) technological advancements are currently being led by the interoperation needs in applications such as smart grids, building energy management systems, electric vehicles, and the Internet of Things. In this paper, alternative control schemes are proposed and compared for the simultaneous transmission of power and digital data through the power circuits of the modules synthesizing a single-phase cascaded H-bridge multilevel inverter. The proposed PLC method does not require any additional circuit elements in the power loop for the PLC implementation. Special focus is paid to the control schemes applied to the H-bridge driving circuits to produce a low total harmonic distortion (THD) without compromising the reliability of data communication. Various parametric simulation models are designed and tested using time-division multiplexing with two variations over the assignment technique for the PLC communication task. The results suggest that the proposed low-bandwidth PLC design is robust enough to provide the required communication fidelity and capable of successfully transmitting the mixed-signal (i.e., power and data) through the power cable under various operating conditions.","PeriodicalId":125740,"journal":{"name":"IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129822651","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: 1