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4th International Conference on Intelligent control, Measurement and Signal Processing, ICMSP 2022

作者： Feng, Dengchao Wang, Jiaxing Wen, Junfeng Wang, Yao Police Uas Combat Training Research Center Shandong Police College Jinan China North China Institute of Aerospace Engineering Dept. of Electronic and Control Engineering Langfang China Shanxi Co. Ltd China Moblie Communications Corporation Taiyuan China School of Management Tianjin University of Technology Tianjin China

ISBN: (数字)9781665486583

ISBN: (纸本)9781665486583

Low altitude safety corridor is not only an important infrastructure construction in China, but also the focus of low altitude strategic competition in the world. UAS is an important part of the development of low altitude safety corridor industry. With the gradual opening of low altitude airspace, the application fields of UAS are greatly expanded. In this paper, the theoretical system of low altitude safety corridor is briefly described. The technical design route of the development of the low altitude safety corridor is introduced. The multi-heterogeneous data acquisition of low altitude airspace and ground environment is used to to realize the accurate sensing and data storage of ground and aerial environment in low altitude airspace. Geographic information system, big data analysis and artificial intelligence are used to achieve accurate analysis of the collected multi-heterogeneous data. Digital twins is used to realize the simulation of low altitude operation and maintenance mechanism, so as to generate intelligent plan, and to build a command and dispatch map. Finally, the integration strategy of low altitude safety corridor and UAS application is explored, including the technological innovation of the combination of low altitude safety corridor operation and UAS application, such as the security strategy in low altitude operation area, the overall operation concept of ground and aerial environment integration, and the relevant laws and regulations. © 2022 IEEE.

关键词： Accident prevention

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Optical Tactile Sensing for Aerial Multi-Contact Interaction: Design, Integration, and Evaluation

arXiv

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arXiv 2024年

作者： Aucone, Emanuele Sferrazza, Carmelo Gregor, Manuel D'Andrea, Raffaello Mintchev, Stefano The Environmental Robotics Laboratory Dept. of Environmental Systems Science ETH Zürich Zürich8092 Switzerland Birmensdorf8903 Switzerland The Robot Learning Lab UC Berkeley BerkeleyCA94704 United States The Institute for Dynamic Systems and Control Dept. of Mechanical and Process Engineering ETH Zürich Zürich8092 Switzerland

Distributed tactile sensing for multi-force detection is crucial for various aerial robot interaction tasks. However, current contact sensing solutions on drones only exploit single end-effector sensors and cannot provide distributed multi-contact sensing. Designed to be easily mounted at the bottom of a drone, we propose an optical tactile sensor that features a large and curved soft sensing surface, a hollow structure and a new illumination system. Even when spaced only 2 cm apart, multiple contacts can be detected simultaneously using our software pipeline, which provides real-world quantities of 3D contact locations (mm) and 3D force vectors (N), with an accuracy of 1.5 mm and 0.17 N respectively. We demonstrate the sensor’s applicability and reliability onboard and in real-time with two demos related to i) the estimation of the compliance of different perches and subsequent re-alignment and landing on the stiffer one, and ii) the mapping of sparse obstacles. The implementation of our distributed tactile sensor represents a significant step towards attaining the full potential of drones as versatile robots capable of interacting with and navigating within complex environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Drones

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Electricity Extraction from Unoccupied Land of Substation

Electricity Extraction from Unoccupied Land of Substation

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International Conference on Energy and Power engineering (ICEPE)

作者： Mohammad Rasel Fahmida Amin Safkat Islam Shah Mohazzem Hossain Dept. of High Voltage Substation Design and Quality Control PowerChina Hubei Electric Engineering Corporation Dhaka Bangladesh Dept.of High Voltage Substation Design and Quality Control Orient Energy Engineering Ltd Dhaka Bangladesh Dept. of Electrical Engineering and Control Systems University of Grenoble Alpes Grenoble France Dept. of Electrical Electronic and Communication Engineering Military Institute of Science and Technology Dhaka Bangladesh

ISBN: (纸本)9781665455787

In developing countries like Bangladesh, the optimum utilization of available sources is a prerequisite to meet up the rising electricity demand in recent years. This paper focuses on extracting clean electrical energy from an open-source, i.e., unoccupied land areas of an electrical utility called substation through analytical approach. The optimally sized PV is installed on those lands to harness electrical energy for further use. It provides significant energy support to the substation and its nearby consumers with better efficiency. This paper encourages increasing this type of solar installation in large numbers of national grid substations to reduce the country's overall electricity demand and shift dependency on traditional fossil fuel-generated electricity.

关键词： Degradation Renewable energy sources Power engineering Substations Government Solar energy Developing countries

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Load Frequency control Scheme controller Design for Isolated and Conventional Two Area Power Systems

Load Frequency Control Scheme Controller Design for Isolated...

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Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Mukesh Soni Amit Mittal Arsalan Muhammad Soomar Pooja Sahoo Karuna Markam Shweta Singh School of Science &Technology Dr. D.Y. Patil Vidyapeeth Pune India Dept. of Allied Sciences Graphic Era Hill University (GEHU) Bhimtal India Electrical & Control Engineering GdanskUniversity of Technology Gdansk Poland Dept. of Electronics Engineering Madhav Institute of Tech. & Science Gwalior India Department of Electronic & Comm. IES College of Technology Bhopal India

The adaptive optimal control approach for the isolated and interconnected power systems, AGC scheme using PI technique is presented in this research. Due to the policy evaluation and policy improvement phases, which analyze and update the cost and control policy, the PI approach can provide adaptive optimal control without using all system states. This is possible through policy evaluation and improvement. An adaptive optimal control strategy based on the PI methodology may be model-free. To complete this work, a comparison of the PI-based and LQR-based schemes efficiency is needed. The adaptive optimum control approach's efficiency has also been studied following several parameter change scenarios. Simulations show that the PI-based adaptive optimum control approach surpasses the LQR-based framework in effectiveness

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Adaptive Power Flow Analysis for Power System Operation Based on Interpretable Graph Deep Learning

SSRN

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SSRN 2024年

作者： Hu, Xiao Yang, Jinduo Gao, Yang Zhu, Mingyang Zhang, Qingyuan Chen, Houhe Zhao, Jin School of Electrical Engineering Northeast Electric Power University Jilin132012 China Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Dept. of Electronic and Electrical Engineering School of Engineering Trinity College Dublin DublinD02PN40 Ireland

High renewable energy penetration in modern power systems brings challenges to power flow calculation. Traditional model-driven methods are hard to handle large-scale power flow with multivariate uncertainty, variable topology, and massive real-time repetitive calculations. With the ability to handle non-Euclidean graph-structured power system data, the graph deep learning shows great potential in modern power flow calculation. However, general graph deep learning based power flow calculation will have limited adaptability for its solely mapping of node information and black-box attributes. In this paper, an edge graph attention network based power flow calculation (EGAT-PFC) model is established with improved adaptability for interpretable power flow analysis. First, the dualmodel structure of node model and edge model is constructed to realize a complete power flow mapping covering all information in power systems. Second, an improved learnable attention coefficient mechanism fusing node and edge features is proposed to ensure global information can be completely considered. Third, mechanisms of extended first-order neighborhood, dynamic normalization and regularization-based loss function are designed to improve training performance. Finally, visualized interpretability is developed to show valuable information of vulnerable nodes and lines of power system operation. The numerical simulation verifies that EGAT-PFC has high accuracy, fast mapping, as well as excellent adaptability to variable topologies. © 2024, The Authors. All rights reserved.

关键词： Mapping

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Adaptive Power Flow Analysis for Power System Operation Based on Graph Deep Learning

SSRN

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SSRN 2024年

Conventional model-driven methods are hard to handle large-scale power flow with multivariate uncertainty, variable topology, and massive real-time repetitive calculations. With the ability to deal with non-Euclidean graph-structured power system data, graph deep learning shows great potential in modern power flow calculation. However, general graph deep learning based power flow calculation has limited adaptability because of its sole mapping of node information and black-box attributes. In this paper, an edge graph attention network based power flow calculation (EGAT-PFC) model is proposed with improved adaptability for power flow analysis of complex system scenarios. First, the dual-model structure of the node model and edge model is constructed to realize a complete power flow mapping covering all information in power systems. Second, an improved learnable attention coefficient mechanism fusing node and edge features is proposed to ensure global information can be completely considered. Third, mechanisms of extended first-order neighborhood, dynamic normalization, and regularization-based loss function are designed to improve training performance. Finally, visualized interpretability is developed to show valuable information of vulnerable nodes and lines of power system operation. The numerical simulation verifies that EGAT-PFC has high accuracy, fast mapping, as well as excellent adaptability to variable topologies. © 2024, The Authors. All rights reserved.

关键词： Mapping

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Innovative Competency-Based Electrical engineering Curriculum 54

Innovative Competency-Based Electrical Engineering Curriculu...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Rehder, Gustavo P. Serrano, Ariana L. C. Grimoni, José B. Brandão, Anarosa A. F. Silva, Magno M. T. Moriya, Henrique T. Panazio, Cristiano M. Barbero, Edson Alayo, Marco I. Gianesi, Irineu G. N. Seabra, Antonio C. Universidade de São Paulo Electronic Systems Department The Escola Politécnica São Paulo Brazil Universidade de São Paulo Electric Automation and Energy Dept. The Escola Politécnica São Paulo Brazil Universidade de São Paulo Computer Engineering and Digital Systems Department The Escola Politécnica São Paulo Brazil Universidade de São Paulo Telecommunications and Control Dept. The Escola Politécnica São Paulo Brazil Á lvares Penteado School of Commerce Foundation São Paulo Brazil Instituto Mauá de Tecnologia São Paulo Brazil

ISBN: (纸本)9798350351507

The Electrical engineering undergraduate program of the Escola Politécnica of the Universidade de São Paulo has created an alternative innovative curriculum path for its freshmen students in 2024. The Competency-based Path emphasizes the development of competencies and skills for the unprecedented technological advancements that necessitate a holistic education for future electrical engineers, preparing them with practical skills for real-world challenges. The program was designed using an innovative methodology and centers around semester-long or year-long integrative projects. These projects bridge the gap between theory and practice, as students deal with real-world challenges while fostering social responsibility. © 2024 IEEE.

关键词： Students

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Decision Method of Operation and Maintenance of CBTC System Based on Knowledge Graph

Decision Method of Operation and Maintenance of CBTC System ...

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Prognostics and System Health Management Conference (PHM-Qingdao)

作者： Linguo Chai Xiaoyu Li Wei ShangGuan Baigen Cai Gaoyun Cheng Min Nie School of Electronic and Information Engineering the State Key Laboratory Rail Traffic Control Beijing Jiaotong University Beijing PR China School of Electronic and Information Engineering Beijing Jiaotong University Beijing PR China Traffic Control Technology Co. Ltd. Beijing PR China Material Supplying Dept. State Grid Beijing Procurement Company Beijing PR China

At present, the failure disposal process for the CBTC system relies heavily on the personal experience of practitioners, and the level of intelligence is at a low level. At the same time, the valuable information in the failure log text is not effectively exploited. Aiming at these problems, this paper proposes a decision-making method for CBTC system operation and maintenance(O&M) based on knowledge graph. First, the knowledge graph construction process is built by combining top-down and bottom-up methods, and the schema layer of the whole failure O&M process is designed by combining expert knowledge. Then, the BERT pre-training model is applied to extract failure entities from the labeled dataset, and the experiment is used to prove the good performance of this model. Next, the extracted entities and their relationships are in the form of nodes and edges for failure knowledge graph is populated and visualized using Neo4j. Finally, the CBTC system O&M knowledge graph is applied to give the failure cause tracing and maintenance suggestion generation method, and the usability of the proposed method is verified with examples, which can effectively assist practitioners to make the O&M decision.

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Non-overshooting output shaping for switched linear systems under arbitrary switching using eigenstructure assignment

arXiv

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arXiv 2024年

作者： Wulff, Kai Honecker, M.C. Schmid, R. Reger, J. Control Systems Group Technische Universtät Ilmenau P.O. Box 10 05 65 IlmenauD-98684 Germany Control Engineering Group Technische Universtät Ilmenau P.O. Box 10 05 65 IlmenauD-98684 Germany Dept. of Electrical and Electronic Engineering University of Melbourne Grattan Street ParkvilleVIC3010 Australia

We consider the analytical control design for a pair of switched linear multiple-input multiple-output (MIMO) systems that are subject to arbitrary switching signals. A state feedback controller design method is proposed to obtain an eigenstructure assignment that ensures that the closed-loop switched system is globally asymptotically stable, and the outputs achieve the non-overshooting tracking of a step reference. Our analysis indicates whether non-overshooting or even monotonic tracking is achievable for the given system and considered outputs and provides a choice of possible eigenstructures to be assigned to the constituent subsystems. We derive a structural condition that verifies the feasibility of the chosen assignment. A constructive algorithm to obtain suitable feedback matrices is provided, and the method is illustrated with numerical examples. © 2024, CC BY-NC-ND.

关键词： MIMO systems

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Object Recognition for Autonomous Driving in Adverse Weather Condition Using Polarized Camera

Object Recognition for Autonomous Driving in Adverse Weather...

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International Conference on control, Mechatronics and Automation (ICCMA)

作者： Min-Ho Ha Chan-Hoe Kim Tae-Hyoung Park Industrial AI Research Center Chungbuk National University Cheongju South Korea Dept. Control and Robot Engineering Chungbuk National University Cheongju South Korea Dept. Intelligent Systems and Robotics Chungbuk National University Cheongju South Korea

ISBN: (纸本)9781665490498

Autonomous driving refers to a vehicle driving by itself without human intervention. An autonomous vehicle must recognize the environment with an attached sensor, make judgments appropriate to the situation, and drive toward its destination. Although many studies have been conducted on autonomous driving in clear weather, the response to bad weather is insufficient because the sensor encounters difficulties recognizing the environment when it is backlight or raining. This study proposes a method for recognizing objects (e.g., vehicles, pedestrians, lanes) based on polarization cameras for safe autonomous driving in backlight conditions or rain. First, the camera’s light input is adjusted, altering its aperture backlight conditions. Then, the polarized image from the camera is synthesized and inputted into the object recognition network. The object detection network used Yolo v5, while the lane detection network used an ultrafast lane detection network. By extracting features from the same backbone, the inference speed of the object recognition network increased. On average, a speed of 23 fps and an object recognition accuracy of over 90% were shown in the Xavier environment.

关键词： Rain Lane detection Roads Vehicle driving Cameras Feature extraction Reduced order systems

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