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Retracted: Intelligent Analysis of Logistics Information Based on Dynamic Network Data 基于动态网络数据的物流信息智能分析
Journal of Control Science and Engineering Pub Date : 2023-08-16 DOI: 10.1155/2023/9820456
Journal of Control Science and Engineering
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引用次数: 0
Research on Reactive Power Optimization Control Method for Distribution Network with DGs Based on Improved Second-Order Oscillating PSO Algorithm 基于改进二阶振荡粒子群算法的dg配电网无功优化控制方法研究
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-07-12 DOI: 10.1155/2023/5813277
Youming Cai, Jingmin Liu, Ning Gao
{"title":"Research on Reactive Power Optimization Control Method for Distribution Network with DGs Based on Improved Second-Order Oscillating PSO Algorithm","authors":"Youming Cai, Jingmin Liu, Ning Gao","doi":"10.1155/2023/5813277","DOIUrl":"https://doi.org/10.1155/2023/5813277","url":null,"abstract":"With the increasing penetration of distributed generation (DG) in the distribution network, the original network structure of the distribution network has been changed. In addition, the randomness and intermittency of renewable power generation will also have an impact on the voltage and power flow of the distribution network. To solve this problem, this paper proposes a reactive power optimization control method for distribution network with DGs based on second-order oscillating particle swarm optimization (PSO) algorithm with a constriction factor. Considering the economic operation of the distribution network, the proposed control method realizes the coordinated operation of the DGs and battery group with the conventional static reactive power compensation device, so as to improve the voltage quality of the distribution network and reduce the system network loss. At the same time, an improved second-order oscillating PSO algorithm is proposed to improve the speed and convergence of the multiobjective algorithm. Finally, the effectiveness of the proposed control method is verified by using MATLAB/Simulink on IEEE 33 bus distribution network with DGs in both static and dynamic situations.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"37 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83009228","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
Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM 基于改进GWO-SVM的自供电系统异常诊断方法
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-06-29 DOI: 10.1155/2023/1981056
Ya jie Li, Shaochong Li, W. Li
{"title":"Abnormal Diagnosis Method of Self-Powered Power Supply System Based on Improved GWO-SVM","authors":"Ya jie Li, Shaochong Li, W. Li","doi":"10.1155/2023/1981056","DOIUrl":"https://doi.org/10.1155/2023/1981056","url":null,"abstract":"In order to solve the problem of low abnormal diagnosis rate of self-powered power supply system, an improved grey wolf optimization-support vector machine (GWO-SVM) algorithm combined with maximal information coefficient (MIC) are proposed. First, the feature sets of 11 kinds of monitoring data are optimized and selected based on MIC for self-powered power supply system. By eliminating redundant variables and insensitive variables, feature variable sets with great influence on abnormal diagnosis are selected. Second, by upgrading the selection method of control parameter \u0000 \u0000 σ\u0000 \u0000 from linear to nonlinear, an improved GWO-SVM algorithm that can take into account both global and local search capabilities is proposed. Furthermore, the optimal feature set which has great influence on abnormal diagnosis is selected as the input of the proposed algorithm, and then the abnormal diagnosis method combining the improved GWO-SVM with MIC is constructed for self-powered power supply system. The specific algorithm flow and step are given. Finally, compared with other algorithm, the simulation experiments show that the GWO-SVM method has a higher accuracy and a higher recall rate for the abnormal diagnosis in the self-powered power supply system.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"461 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76354960","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
Historical Background of the Origin of the Speeddroop, Additional Control Signals and Analogic Retrofit of a Governor of a Francis Turbine, Using Operational Amplifier IC741 速度下降起源的历史背景,附加控制信号和混流式涡轮调速器的模拟改造,使用运算放大器IC741
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-04-27 DOI: 10.11648/j.cse.20230701.12
Jose Luiz Guarino, Jose Flavio Silveira Feiteira
{"title":"Historical Background of the Origin of the Speeddroop, Additional Control Signals and Analogic Retrofit of a Governor of a Francis Turbine, Using Operational Amplifier IC741","authors":"Jose Luiz Guarino, Jose Flavio Silveira Feiteira","doi":"10.11648/j.cse.20230701.12","DOIUrl":"https://doi.org/10.11648/j.cse.20230701.12","url":null,"abstract":"","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"104 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80864890","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
Calculation of RMS Current Load on DC-Link Capacitors for Multiphase Machine Drives under Carrier-Phase Shift Control 载波移相控制下多相电机直流电容有效值电流负载的计算
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-04-25 DOI: 10.1155/2023/6909403
Zhigang Zhang, Pengcheng Zhang, Yang Zhang, Wenjuan Zhang, Mengdi Li, Zichen Xiong
{"title":"Calculation of RMS Current Load on DC-Link Capacitors for Multiphase Machine Drives under Carrier-Phase Shift Control","authors":"Zhigang Zhang, Pengcheng Zhang, Yang Zhang, Wenjuan Zhang, Mengdi Li, Zichen Xiong","doi":"10.1155/2023/6909403","DOIUrl":"https://doi.org/10.1155/2023/6909403","url":null,"abstract":"The reliability and economy of dc-link capacitors are important concerns in multiphase drive systems. Due to the parallel connection of several converters, the dc-link capacitors are subjected to a higher RMS current, and the root mean square (RMS) current of dc-link capacitors is an important reference standard to determine its lifetime, cost, and volume. In this paper, the RMS current of dc-link capacitor is calculated by using the dual Fourier integral method and the effect of carrier interleave is studied. Meanwhile, the modulation ratio, harmonic sidebands, and switching frequency are also considered. In order to optimize the reliability and economy of the multiphase drive system, a Cotes method combined with carrier-phase shifting technology (CPST) for calculating RMS current of the dc-link capacitor is proposed. The proposed method can provide optimization guidance for the design of dc-link capacitors. Finally, the analytical and experiment results are compared with the existing methods, and the experimental results verify the effectiveness of the proposed method.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"27 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81710163","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
UAV Tilt Photography Control for Numerical Simulation of High and Steep Rock Slopes 高陡岩质边坡数值模拟的无人机倾斜摄影控制
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-04-20 DOI: 10.1155/2023/7489283
Yani Wang, Yinpeng Zhou, Bo Wang
{"title":"UAV Tilt Photography Control for Numerical Simulation of High and Steep Rock Slopes","authors":"Yani Wang, Yinpeng Zhou, Bo Wang","doi":"10.1155/2023/7489283","DOIUrl":"https://doi.org/10.1155/2023/7489283","url":null,"abstract":"In order to provide accurate image information for the analysis and treatment of dangerous rocks and rockfalls during the early investigation, a UAV tilt photography control method for numerical simulation of high and steep rock slopes is proposed. Based on the UAV tilting photography technology, the slope section was obtained through a real 3D modeling and poststage point cloud data processing. Numerical simulation is used to study the motion characteristics of dangerous rock falling in a high and steep slope of a railway station. This essay introduces the application of a UAV tilting photography and real 3D modeling technology in the process of rock fall analysis and realizes the real scene restoration of the site. The point cloud data of the site is obtained, and the processing process of the point cloud is introduced in detail. The slope section of the site was obtained based on the point cloud, and RocFall software was used to obtain the motion characteristics of dangerous rock falling (falling trajectory, bouncing height impact energy, and impact velocity). The simulation results show that because of the rugged slope, the falling rocks collide and rebound on the slope for many times. In addition, near the bottom of the slope, there is a steep cliff with a height of 136.21 m, which is approximately 54° from the horizontal line, causing the falling rock to bounce and eventually fall at a higher height. It moves to the bottom of the slope and bounces off the level of the railway line before finally settling on the railway road. The maximum bounce height of falling rock in the process of slope rolling motion reaches 30 m. When falling rock moves near the railway line (coordinate is on the right side of zero), the bounce height is 15∼25 m, which threatens the safety of the railway operation. Conclusion. The UAV tilt photography technology can be well applied to the analysis of rockfall motion characteristics of dangerous rocks, and provide an accurate cross-section data information for the study of rockfall motion characteristics of dangerous rocks.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"18 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84456041","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
Robot Fault Detection Based on Big Data 基于大数据的机器人故障检测
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-04-04 DOI: 10.1155/2023/8375382
Fei Luo
{"title":"Robot Fault Detection Based on Big Data","authors":"Fei Luo","doi":"10.1155/2023/8375382","DOIUrl":"https://doi.org/10.1155/2023/8375382","url":null,"abstract":"In order to improve the reliability of robot electrical fault detection and diagnosis, the author proposes a robot electrical fault detection and diagnosis method based on deep learning. Taking the return power and active power as constraints, the electrical fault data collection of the robot is carried out. Taking the resonant inductance and resonant capacitance of the robot electrical equipment as identification parameters, we conduct electrical fault differential feature mining. The fault features are extracted according to the time-delay distribution sequence of the electrical fault data of the robot, and the electrical fault detection and diagnosis results are output by using the deep learning function. Simulation results show that the author's method has a high accuracy probability for robot electrical fault diagnosis. The author's method is on average 14.7% higher than the neural network-based method and 24.5% higher than the expert system-based method. The accuracy rate of the author's method for robot electrical fault diagnosis is high. The author’s method is 16.6% higher than the neural network-based method on average and 34.2% higher than the expert system-based method. It is proved that the robot electrical fault detection and diagnosis based on deep learning has high accuracy and short time.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"167 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89426945","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
Motion Trajectory Error of Robotic Arm Based on Neural Network Algorithm 基于神经网络算法的机械臂运动轨迹误差
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-04-04 DOI: 10.1155/2023/3958434
B. Xu, Chen Sem-Lin
{"title":"Motion Trajectory Error of Robotic Arm Based on Neural Network Algorithm","authors":"B. Xu, Chen Sem-Lin","doi":"10.1155/2023/3958434","DOIUrl":"https://doi.org/10.1155/2023/3958434","url":null,"abstract":"In order to solve the problems of unstable motion and large trajectory tracking error of the manipulator when it is disturbed by the outside world, the author proposes an adaptive neural network manipulator motion trajectory error method. The author gives the dynamic equation of the manipulator and uses the positive feedback neural network to study the dynamic characteristics of the manipulator. An adaptive neural network control system is designed, and the stability and convergence of the closed-loop system are proved by the Lyapunov function. A schematic diagram of the manipulator model is established, and MATLAB/Simulink software is used to simulate the dynamic parameters of the manipulator. At the same time, it is compared and analyzed with the simulation results of the PID control system. Simulation results show that in robot arm 3, the expected motion trajectory is θ3 = 0.4cos(2πt), the initial condition θ(0) = [000]τ, the control parameter K = diag(40,40),40), the disturbance parameter τ’ = 20cos(πt), robot arm link parameters l1 = 0.62 m, l2 = 0.41 m, l3 = 0.34 m, m1 = 3.5, m2 = 2.5 kg, m3 = 2 kg, g = 9.82 m/s2, under t = 2s, the motion trajectory of the robotic arm is disturbed by the outside world, and the adaptive neural network is used to control the motion trajectory with a small tracking error, input torque ripple is small. Conclusion. The manipulator adopts the adaptive neural network control method, which can improve the control accuracy of the motion trajectory and weaken the jitter phenomenon of the manipulator motion.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83001158","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: 2
Retrofit of a Governor Electronic-Analogic of a Francis Turbine of 180 MW of Decade of 1960 Using Microcontroller Arduino Due 用Arduino Due微控制器改造1960年代180mw混流式水轮机调速器电子模拟装置
IF 1.7
Journal of Control Science and Engineering Pub Date : 2023-02-16 DOI: 10.11648/j.cse.20230701.11
Jose Luiz Guarino, Jose Flavio Silveira Feiteira
{"title":"Retrofit of a Governor Electronic-Analogic of a Francis Turbine of 180 MW of Decade of 1960 Using Microcontroller Arduino Due","authors":"Jose Luiz Guarino, Jose Flavio Silveira Feiteira","doi":"10.11648/j.cse.20230701.11","DOIUrl":"https://doi.org/10.11648/j.cse.20230701.11","url":null,"abstract":": This paper describes the retrofit of a governor electronic-analogical of a Francis turbine of a synchronous generator of the decade of 1960. The author has many years of experience in maintenance in governors of hydroelectric power plants including excitation systems. Governors are responsible to maintain constant the frequency of a power electric net. The original model of the governor in question was obtained in local field tests, not related in this paper. In this retrofit, time constants were maintained to respect the original project and avoid hydraulic harmful and dangerous transitory problems. The original continuous model of the governor was simplified toa a second order model. The second order continuous model was emulated to a discrete system. The difference equation was created and microcontroller Arduino Due was programming. The digital controller produced, was syntonized to cancel the mathematical function of the servomotor, to reduce the grade of the resulted system obtaining a second order system. The hydraulic part of the governor was simulated using 741 operational amplifiers. During the tests in the workbench the author burned two Arduino’s electronic cards so it was necessary to create the electronic interface between Arduino and the 741 amp op including over and under voltage protection. The complete set was successfully tested in workbench. The mathematical models were priory simulated with Matlab-Simulink and there were the corresponding electronic simulations in workbench that confirmed the results. This retrofit solution, using Arduino Due, is of low cost compared to traditional manufacturers.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"46 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86698521","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 Artificial Intelligence Technology in Computer Network Security Communication 人工智能技术在计算机网络安全通信中的应用
IF 1.7
Journal of Control Science and Engineering Pub Date : 2022-07-21 DOI: 10.1155/2022/9785880
Fu-lei Li
{"title":"Application of Artificial Intelligence Technology in Computer Network Security Communication","authors":"Fu-lei Li","doi":"10.1155/2022/9785880","DOIUrl":"https://doi.org/10.1155/2022/9785880","url":null,"abstract":"In order to cope with the frequent challenges of network security issues, a method of applying artificial intelligence technology to computer network security communication is proposed. First, within the framework of computer network communication, an intelligent protocol reverse analysis method is proposed. By converting the protocol into an image and establishing a convolutional neural network model, artificial intelligence technology is used to map the data to the protocol result. Finally, use the model to test the test data to adjust the model parameters and optimize the model as much as possible. The experimental results show that compared with the test model, the results obtained after training with the deep convolutional neural network model in this paper have increased the accuracy by 2.4%, reduced the loss by 38.2%, and reduced the running time by 42 times. The correctness and superiority of the algorithm and model are verified.","PeriodicalId":46052,"journal":{"name":"Journal of Control Science and Engineering","volume":"48 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2022-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83175252","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: 3
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