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3rd international conference on Optics, Computer Applications, and Materials Science, CMSD 2023

作者： Kurbanov, Janibek F Yaronova, Natalya V. Xidirov, Jasurjon E Achilov, Oybek R Tashkent State Transport University 1 Temiryolchilar Street Mirabad district Tashkent100167 Uzbekistan

ISBN: (纸本)9781510674486

In the field of automation and telemechanics, the main task is to improve the automatic locomotive signaling system (ALS), including the creation of a complex of remote measuring devices using wireless, microprocessor and digital technologies to eliminate malfunctions on railway sections of automatic and semi-Automatic locking. This article presents an analysis of errors in traffic light indicators and the automatic locomotive signaling system by month from the time of the year, which affect the speed of trains, namely, due to a false indicator, the speed decreases, this leads to lagging behind schedule, thereby due to the lack of timely arrival of trains, the company incurs financial losses. All malfunctions arising from a system failure are represented by mathematical expressions, on the basis of which recommendations for elimination are given. A module for receiving information from the locomotive's ALS was developed based on modern wireless technologies, and for the accuracy of checking the system, a stand based on the locomotive's ALS blocks for measuring signals was developed, which corresponded to the exact readings of the parameters of the ALS code signals. The developed module provides an opportunity to instantly notify the site's electromechanics of identified deficiencies in the ALS system. © 2024 SPIE. All rights reserved.

关键词： Railroads

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Review of Low Voltage Ride Through Testing Techniques for Wind Turbine Generators 3rd

Review of Low Voltage Ride Through Testing Techniques for Wi...

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3rd international Joint conference on Energy, Electrical and Power engineering, CoEEPE 2023

作者： Lei, Xiao Li, Xuzhe Yao, Weiwei Tian, Xinwen Yuan, Jiaxin Laboratory of Hydro-Wind-Solar Multi-Energy Control Coordination China Yangtze Power Co. Ltd Wuhan China Laboratory of Hydro-Wind-Solar Multi-Energy Control Coordination Wuhan University Wuhan China

ISBN: (纸本)9789819739394

With the increasing global share of wind power and the growing installed capacity of grid-connected wind turbines in China, it is of utmost importance to enhance the low voltage ride through (LVRT) capability of wind turbine generators to avoid significant loss of manpower and economic benefits caused by grid disconnection. This paper first analyses the transient processes of wind turbine topologies after a voltage drop and introduces the latest LVRT testing technical specifications from major countries around the world. Subsequently, it comprehensively analyses and summarizes the advantages and disadvantages of various testing simulation devices. Finally, it provides a prospective outlook on the future development direction of LVRT testing techniques for wind turbine generators, considering both technical standards and testing equipment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wind Turbine Generators

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Predictive Performance of EV Charging Behaviour in COVID-19 3

Predictive Performance of EV Charging Behaviour in COVID-19

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3rd IEEE international conference on Sustainable Energy and Future Electric Transportation, SeFet 2023

作者： Gupta, Manvi Mittal, Jishnu Tomar, Anuradha Netaji Subhas University of Technology Electrical Engineering New Delhi India Netaji Subhas University of Technology Instrumentation and Control Engineering New Delhi India

ISBN: (纸本)9798350319972

Transportation is an essential prerequisite for modern life, however, the conventional combustion engine is rapidly losing its relevance. Vehicles powered by petrol and diesel emit a substantial amount of pollutants and are currently being rapidly replaced by fully electric vehicles (EVs). These EVs are emission-free and significantly more eco-friendly. The COVID-19 pandemic has had a significant impact on the global EVs market. The widespread adoption of EVs faces various challenges, including vehicle scheduling due to the limited EV charging facilities. Smart scheduling algorithms can address this issue by managing to improve EV scheduling by utilizing tools and algorithms fueled by data-driven approaches to predict EV charging demand. Previous research has utilized historical EV charging data to predict the behavior of departure time and energy needs. However, unexpected events like a pandemic can lead to changes in behavior, making predictions more challenging. This paper proposes using pre-COVID and COVID-period historical charging data to predict EV session duration using machine learning algorithms like Decision Tree Regressor, XGBoost, and Deep Neural Networks. XGBoost achieved the best predictive performance, with R2 scores of 0.99 for session duration, outperforming existing literature. The study demonstrates significant improvement in both predictions compared to previous work and conducts a comparative analysis of EV behavior during normal and unexpected circumstances. Overall as a result of the COVID-19 pandemic, the global EV market has experienced a decline in growth. With factory closures, supply chain disruptions, and reduced consumer demand, the production and sales of EVs have been negatively impacted. © 2023 IEEE.

关键词： Forecasting

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Robust Neural control for Distributed Formation of UAVs Under Uncertain Disturbances 1

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3rd international conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Li, Chenwei Xie, Ailing Zhou, Jianshan Tian, Daxin Duan, Xuting Sheng, Zhengguo Zhao, Dezong Lu, Caixia Key Laboratory of Technology on Intelligent Transportation Systems Ministry of Science and Technology Beijing100088 China School of Transportation Science and Engineering Beihang University Beijing100191 China Department of Engineering and Design University of Sussex BrightonBN2 4AT United Kingdom James Watt School of Engineering University of Glasgow Glasgow United Kingdom China North Artificial Intelligence and Innovation Research Institute Beijing100071 China

ISBN: (数字)9789819710836

ISBN: (纸本)9789819710829

Multi-quadrotor formations have received wide attention in recent years because of their mobility, flexibility, ability to perform complex tasks instead of humans and higher performance than a single quadrotor. However, formation flight is inevitably affected by model uncertainties and external disturbances, which significantly challenge the design of quadrotor formation controllers. Traditional robust controllers tend to limit the performance of the intelligence, and deep reinforcement learning can achieve high performance in control tasks but needs more robustness. This paper uses a neural network-based robust control strategy to control a quadrotor formation to ensure robustness and performance under uncertainty disturbances. The formation is modeled using the leader-follower approach. We conducted simulation experiments to verify the feasibility of the method. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Robust control

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A Compensation Method for Lost Trajectories of ORB-SLAM3 with DROID-VO

A Compensation Method for Lost Trajectories of ORB-SLAM3 wit...

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Computer, control and robotics (ICCCR), international conference on

作者： Kairong Liu Yong Fan Jianmei Su Ling Wu Kexin Zhang School of Computer Science and Technology Southwest University of Science and Technology Sichuan China

Under extreme conditions such as pure rotation, motion blur and poor texture, ORB-SLAM3 cannot perform pose estimation well which leads to trajectory loss inevitably. In this paper, we present a robust compensation method which uses DROID-VO to generate lost trajectories and inserts them into ORB-SLAM3 accurately. Experimental results on EuRoC, Tartanair and TUM-RGBD datasets indicate that the proposed method achieves hizher coverage and can adapt to more conditions.

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Analysis and Enhancement Strategies of Private Undergraduate Students' Learning Effect of Principle of Singlechip Based on Online and Offline Mixed-mode Teaching: K-Fold Cross-Validation Method 3

Analysis and Enhancement Strategies of Private Undergraduate...

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3rd international conference on Intelligent Computing, Communication and Convergence, ICI3C 2023

作者： Ren, Yan Wang, Yunjiang Shenyang Institute of Science and Technology Department of Information and Control Engineering Shenyang China Shenyang Aerospace University School of Mechatronics Engineering Shenyang China

ISBN: (纸本)9798350343922

The principle of single chip microcomputer is a professional basic course with "program design"as the main line, and it is also a very practical course, involving a lot of practical engineering applications. For private undergraduate colleges, there are some difficulties and challenges in the teaching process. In this paper, k-fold cross-verification method is adopted to analyze and improve the learning effect of singlechip microcomputer based on the mixed mode of online and offline teaching. This is a student-centered, teacher-guided, student-independent learning as the purpose, fully mobilize students' subjective initiative and enthusiasm, improve learning efficiency and effect of teaching methods. The experimental results show that this method can improve the students' motivation score to 85 points, which was 12 points higher than the previous maximum score of 73 points. At the same time, innovation ability, practical ability and sense of achievement have also improved. It can be seen that the method adopted in the article has a good effect in improving the learning effect. © 2023 IEEE.

关键词： Microcomputers

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The Leader-Follower Joint Space Synchronous Impedance control for Coordinated Operation in Nuclear Industry

The Leader-Follower Joint Space Synchronous Impedance Contro...

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Computer, control and robotics (ICCCR), international conference on

作者： Xiaoyu Zhao Yuyao Tang Yapeng Yang Qi Lv Nuclear Emergency and Nuclear Safety Department China Institute for Radiation Protection Taiyuan China

Coordinated operation is a common task for the dual-arm robot system in nuclear industry, and the trajectory tracking performance and inner torque are both important indications for the coordinated operation. However, the radiation affects the application of end force/torque sensor and it is practicable to compromising the indications in the joint space. In this paper, leader-follower joint space synchronous impedance control is proposed to compromise the two indications. The dual-arm system is controlled by the leader-follower mode and controller is designed to satisfy the pose and force constraints. Simulation is carried out and the results show considerable performance.

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Optimization of Clustering, and QOS Routing in Wireless Multicast Ad-Hoc Networks with Topology control 3

Optimization of Clustering, and QOS Routing in Wireless Mult...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Ghumman, Sukhman Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350319125

In this study, we provide a novel approach to multicast wireless ad hoc network routing with cluster QoS optimization. The notion of topology compression is used to quantify the effect of multicast heterogeneity on scheduling by use of a compressed multiplex topology matrix. Topology matrices are defined by first identifying all feasible multicast pathways, including network-coded paths. In a conflict-free environment provided by careful scheduling, a selection of these pathways with optimal rates is selected to optimize feasible throughput and capacity per sum of transmission powers along the route. As a result, this optimization yields not one but two improvements: one in the form of performance enhancement due to planning on a condensed network topology, and another in the form of mixed route selection optimizations that strike a fine balance between multicast variety and network coding. As an example, we provide the numerical findings for a basic wireless butterfly network. If throughput is the only metric of importance, then either a network coded design or simple routing may be optimal, depending on the specifics of the system. However, a collection of simple routing pathways is optimal if throughput is prioritized above power consumption. In this study, we examine the problem of energy-efficient topology management in ad hoc wireless connections. We create an Energy Effective Topology controller method that incorporates a pertinent QoS Routing system in order to identify a network architecture that has maximum network lifespan fulfill QoS criteria, which includes traffic needs, hop bound, and bandwidth. The combined analytical along with numerical findings show that, when compared to algorithms that are solely concerned with reducing energy consumption, this optimal method can achieve the optimum network lifespan, which is a genuine period of time and more important and reasonable than merely reducing energy consumption. © 2023 IEEE.

关键词： and Topology control Optimization of Clustering QOS Routing Wireless Multicast Ad-Hoc Networks

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Performance Analysis of Load Frequency control for Power Plants Using Different Optimization Techniques

Performance Analysis of Load Frequency Control for Power Pla...

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international conference on robotics,Electrical and Signal Processing Techniques (ICREST)

作者： Niloy Goswami Abu Hena Md. Shatil Electrical and Electronics Engineering Department American International University-Bangladesh(AIUB) Dhaka Bangladesh

In this paper, several optimization techniques including the Particle Swarm Optimization (PSO) technique, the Genetic Algorithm (GA), and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are applied to determine the most efficient output for load frequency control. These optimization techniques analyze the optimal level of system performance. The goal of this paper is to identify the most effective optimization technique for this sophisticated LFC system. In this research, three strategies (PSO, GA, ANFIS) are used in the LFC system to analyze frequency fluctuation and compare the load change rate. The model consists of the transfer function of the governor, turbine, rotating mass, and load. In this analysis, the ideal performance is examined across three separate case scenarios. The MATLAB/SIMULINK software simulates the performance analysis, which offers more realistic data and is generally preferred in this sort of optimization strategy work.

关键词： Fluctuations System performance Simulation Transfer functions Software Performance analysis Optimization

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Meta-learning-based multi-objective PSO model for dynamic scheduling optimization

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ENERGY REPORTS 2023年 9卷 1227-1236页

作者： Lv, Zheng Liao, Zherun Liu, Ying Zhao, Jun Dalian Univ Technol Key Lab Intelligent Control & Optimizat Ind Equipm Minist Educ Dalian 116024 Peoples R China

The by-product gas is an important secondary energy in the iron and steel industry. It is important to make the by-product gas's utilization efficient and reasonable,which is the key to improve the economic efficiency and the level of energy conservation and emission reduction. Aiming at the problems of complex dynamic changes, difficult to accurately model and difficult to predict real-time traffic in gas energy system, this paper proposes an optimal scheduling method based on meta-learning multi-objective particle swarm optimization algorithm. The gas energy optimization scheduling problem is modeled as a multi-objective dynamic scheduling optimization problem. The difficulty of this problem is to comprehensively consider multiple indicators, continuously adapt to the change of the objective function over time, and track the changing Pareto optimal solution set. One of the promising solutions is to build prediction models with better performance under dynamic changes. The model we propose makes full use of the optimization results and the experience information of the optimization process in the historical optimization task. We propose a dynamic parameter initialization method based on meta-learning by starting multiple historical optimization tasks at the same time. Thus,the comprehensive parameters of different tasks are obtained, and a general and best base parameter is learned. Experiments show that the proposed model has better convergence and accuracy than the conventional algorithm. (c) 2023 Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Energy scheduling Meta-learning Multi-objective dynamic optimization Pre-knowledge learning

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