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Статті в журналах з теми "Machine vector control"

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Автор: Grafiati

Опубліковано: 14 березня 2023

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1

Wang, De Cheng, Er Hao Liu, and Hui Lin. "One Approach for Direct Torque Control Switching Voltage Vector Selection." Applied Mechanics and Materials 246-247 (December 2012): 867–71. http://dx.doi.org/10.4028/www.scientific.net/amm.246-247.867.

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Анотація:

Direct torque control selected switching voltage vector according to torque hysteresis comparator output, flux hysteresis comparator output, and sector. One switching voltage vector selection approach was proposed. It used support vector regression machine to carry out direct torque control switching voltage vector selection. The selection of eight switching voltage vectors was an eight classification problem. This classification problem was changed into regression problem by support vector regression machine. The nonlinear function used for switching voltage vector selection was gained by support vector regression machine training. Asynchronous motor direct torque control simulation result shows feasibility and effectivity of proposed method.

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2

NEZLI, Lazhari, and Omar Zouaid. "Sliding mode control of a Five-Phase Series- Connected Two-Motor Drive." Algerian Journal of Signals and Systems 1, no. 1 (February 2, 2021): 59–68. http://dx.doi.org/10.51485/ajss.v1i1.19.

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Анотація:

In this work, we study vector control and sliding mode control of series-connected five-phase two asynchronous machines supplied with a three levels inverter. After presentation of multiphase machines, we worked out the mathematical model of five phase asynchronous machine supplied with voltage inverter. Application of Park transformation reduces considerably the mathematical model of machine. After, we applied vector control and sliding mode control to the five-phase induction machine. After that, we study a multi-machine system which comport five-phase two asynchronous machines supplied with a single voltage inverter. In the last, we had the independent vector control and the sliding mode control of series-connected five-phase two asynchronous machines. We observe that an appropriate transposition of phase’s order permits an independent control of two machines.

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3

Vasconcelos, Carlos, Richard Stephan, and Antonio Ferreira. "Study Of The Cascaded Doubly Fed Induction Machine Dynamics Under Vector Control." Eletrônica de Potência 23, no. 1 (March 1, 2018): 39–46. http://dx.doi.org/10.18618/rep.2018.1.2719.

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4

Amman, Hans M. "Nonlinear control simulation on a vector machine." Parallel Computing 10, no. 1 (March 1989): 123–27. http://dx.doi.org/10.1016/0167-8191(89)90084-7.

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5

Yamamoto, Maeri, Epifanio Bagarinao, Itaru Kushima, Tsutomu Takahashi, Daiki Sasabayashi, Toshiya Inada, Michio Suzuki, Tetsuya Iidaka, and Norio Ozaki. "Support vector machine-based classification of schizophrenia patients and healthy controls using structural magnetic resonance imaging from two independent sites." PLOS ONE 15, no. 11 (November 24, 2020): e0239615. http://dx.doi.org/10.1371/journal.pone.0239615.

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Анотація:

Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support vector machines can classify patients and healthy controls by detecting subtle and spatially distributed patterns of structural alterations. We aimed to use a support vector machine to distinguish patients with schizophrenia from control participants on the basis of structural magnetic resonance imaging data and delineate the patterns of structural alterations that significantly contributed to the classification performance. We used independent datasets from different sites with different magnetic resonance imaging scanners, protocols and clinical characteristics of the patient group to achieve a more accurate estimate of the classification performance of support vector machines. We developed a support vector machine classifier using the dataset from one site (101 participants) and evaluated the performance of the trained support vector machine using a dataset from the other site (97 participants) and vice versa. We assessed the performance of the trained support vector machines in each support vector machine classifier. Both support vector machine classifiers attained a classification accuracy of >70% with two independent datasets indicating a consistently high performance of support vector machines even when used to classify data from different sites, scanners and different acquisition protocols. The regions contributing to the classification accuracy included the bilateral medial frontal cortex, superior temporal cortex, insula, occipital cortex, cerebellum, and thalamus, which have been reported to be related to the pathogenesis of schizophrenia. These results indicated that the support vector machine could detect subtle structural brain alterations and might aid our understanding of the pathophysiology of these changes in schizophrenia, which could be one of the diagnostic findings of schizophrenia.

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6

MURATA, Toshiaki, Takeshi TSUCHIYA, and Ikuo TAKEDA. "Vector Control for Induction Machine by Primary Flux Linkage Control." Transactions of the Society of Instrument and Control Engineers 25, no. 11 (1989): 1194–201. http://dx.doi.org/10.9746/sicetr1965.25.1194.

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7

Alazrag, A., and L. Sbita. "Asynchronous Machine with Wind Turbine IRFO Control." WSEAS TRANSACTIONS ON POWER SYSTEMS 17 (June 30, 2022): 141–54. http://dx.doi.org/10.37394/232016.2022.17.15.

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Анотація:

The paper deals with a squirrel cage induction generator connected to the grid through a back-to-back converter driven by vector control. The stator-side converter controls the generator torque by means of an indirect vector control scheme. In order to reduce the system dependence from the mechanical system behavior, a torque loop is used in the current reference calculations. The battery energy storage system (BESS) plays a fundamental role in controlling and improving the efficiency of renewable energy sources. Stochasticity of wind speed and reliability of the main system components are considered. The grid-side converter controls the DC bus voltage and the reactive power in order to accomplish the grid codes. Speed control using flow directional control, indirect conventionally uses proportional integral (PI) type current regulators, which achieve satisfactory objectives on torque and flow dynamics. The objective of this article is to present an indirect vector control strategy with oriented rotor flux using current regulators of the proportional integral (PI) type, applied to an asynchronous machine supplied by a voltage inverter, capable of supplying during restrictive stresses, more satisfactory torque and flux responses. The obtained simulation results upon simulation tests of the global system are developed under the MATLAB / Simulink environment and are satisfactory.

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8

MURATA, Toshiaki, Takeshi TSUCHIYA, and Ikuo TAKEDA. "Vector Control for Induction Machine by State Feedback." Transactions of the Society of Instrument and Control Engineers 24, no. 6 (1988): 596–602. http://dx.doi.org/10.9746/sicetr1965.24.596.

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9

Wang, Syed A. Nasar, Ion Boldea, Congxiao. "Vector Control of Three-Phase Flux Reversal Machine." Electric Machines & Power Systems 28, no. 2 (February 2000): 153–66. http://dx.doi.org/10.1080/073135600268432.

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10

Wauters, Mathieu, and Mario Vanhoucke. "Support Vector Machine Regression for project control forecasting." Automation in Construction 47 (November 2014): 92–106. http://dx.doi.org/10.1016/j.autcon.2014.07.014.

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11

Bao, Zhejing, and Youxian Sun. "Support vector machine-based multi-model predictive control." Journal of Control Theory and Applications 6, no. 3 (August 2008): 305–10. http://dx.doi.org/10.1007/s11768-008-6082-6.

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12

Li, Ming Hui, and Zheng Qi Li. "Based on Vector Control of All-Electric Injection Molding Machine Control System Design." Advanced Materials Research 490-495 (March 2012): 2210–14. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.2210.

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Анотація:

According to the all-electric injection molding machine control system requirements, the vector control applied to the permanent magnet synchronous motor control, we propose a fully electric injection molding machine control system design, through analysis and research that can further improve the program precise all-electric injection molding machine control, its stability, high reliability, to better meet the all-electric injection molding machine of precision and stability requirements.

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13

Polyak, Roman, Shen-Shyang Ho, and Igor Griva. "Support vector machine via nonlinear rescaling method." Optimization Letters 1, no. 4 (November 11, 2006): 367–78. http://dx.doi.org/10.1007/s11590-006-0033-2.

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14

Mahmoud, Tarek. "Adaptive control scheme based on the least squares support vector machine network." International Journal of Applied Mathematics and Computer Science 21, no. 4 (December 1, 2011): 685–96. http://dx.doi.org/10.2478/v10006-011-0054-6.

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Adaptive control scheme based on the least squares support vector machine networkRecently, a new type of neural networks called Least Squares Support Vector Machines (LS-SVMs) has been receiving increasing attention in nonlinear system identification and control due to its generalization performance. This paper develops a stable adaptive control scheme using the LS-SVM network. The developed control scheme includes two parts: the identification part that uses a modified structure of LS-SVM neural networks called the multi-resolution wavelet least squares support vector machine network (MRWLS-SVM) as a predictor model, and the controller part that is developed to track a reference trajectory. By means of the Lyapunov stability criterion, stability analysis for the tracking errors is performed. Finally, simulation studies are performed to demonstrate the capability of the developed approach in controlling a pH process.

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15

Chiuso, A., and G. Pillonetto. "System Identification: A Machine Learning Perspective." Annual Review of Control, Robotics, and Autonomous Systems 2, no. 1 (May 3, 2019): 281–304. http://dx.doi.org/10.1146/annurev-control-053018-023744.

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Анотація:

Estimation of functions from sparse and noisy data is a central theme in machine learning. In the last few years, many algorithms have been developed that exploit Tikhonov regularization theory and reproducing kernel Hilbert spaces. These are the so-called kernel-based methods, which include powerful approaches like regularization networks, support vector machines, and Gaussian regression. Recently, these techniques have also gained popularity in the system identification community. In both linear and nonlinear settings, kernels that incorporate information on dynamic systems, such as the smoothness and stability of the input–output map, can challenge consolidated approaches based on parametric model structures. In the classical parametric setting, the complexity of the model (the model order) needs to be chosen, typically from a finite family of alternatives, by trading bias and variance. This (discrete) model order selection step may be critical, especially when the true model does not belong to the model class. In regularization-based approaches, model complexity is controlled by tuning (continuous) regularization parameters, making the model selection step more robust. In this article, we review these new kernel-based system identification approaches and discuss extensions based on nuclear and [Formula: see text] norms.

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16

Zouaid, Omar, and Lazhari Nezli. "Control with Sliding Mode of a Five-Phase Series-Connected Two-asynchronous Motor Drive." International Journal of Energetica 3, no. 1 (June 30, 2018): 18. http://dx.doi.org/10.47238/ijeca.v3i1.61.

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Анотація:

In this paper, we study sliding mode control of series-connected five-phase two asynchronous machines supplied with a three levels inverter. After presentation of multiphase machines, we worked out the mathematical model of five phase asynchronous machine supplied with voltage inverter. Application of Park transformation reduces considerably the mathematical model of machine. After, we applied vector control and sliding mode control to the five-phase induction machine. After that, we study a multi-machine system, which comport five-phase two asynchronous machines supplied with a single voltage inverter.In the last, we had the sliding mode control of series-connected five-phase two asynchronous machines. Simulations are presented to show the effectiveness of the control strategy. We observe that an appropriate transposition of phase’s order permits an independent control of two machines.

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17

Liu, Xuanyu, and Kaiju Zhang. "Earth pressure prediction in sealed chamber of shield machine based on parallel least squares support vector machine optimized by cooperative particle swarm optimization." Measurement and Control 52, no. 7-8 (May 10, 2019): 758–64. http://dx.doi.org/10.1177/0020294019840720.

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Анотація:

Earth pressure in sealed chamber is affected by multisystem and multifield coupling during shield tunneling process, so it is difficult to establish a mechanism earth pressure control model. Therefore, a data-driven modeling method of earth pressure in sealed chamber is proposed, which is based on parallel least squares support vector machine optimized by parallel cooperative particle swarm (parallel cooperative particle swarm optimization-partial least squares support vector machine). The vectors are parallel studied according to different hierarchies firstly, then the initial classifiers are updated by using cross-feedback method to retrain the vectors, and finally the vectors are merged to obtain the support vectors. The parameters of least squares support vector machine are optimized by the parallel cooperative particle swarm optimization, so as to predict quickly for large-scale data. Finally, the simulation experiment is carried out based on in-site measured data, and the results show that the method has high computing efficiency and prediction accuracy. The method has directive significance for engineering application.

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18

Yalsavar, Maryam, Paknoosh Karimaghaei, Akbar Sheikh-Akbari, Pancham Shukla, and Peyman Setoodeh. "Support vector machine and its difficulties from control field of view." Transactions of the Institute of Measurement and Control 43, no. 9 (February 25, 2021): 1833–42. http://dx.doi.org/10.1177/0142331220977436.

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The application of the support vector machine (SVM) classification algorithm to large-scale datasets is limited due to its use of a large number of support vectors and dependency of its performance on its kernel parameter. In this paper, SVM is redefined as a control system and iterative learning control (ILC) method is used to optimize SVM’s kernel parameter. The ILC technique first defines an error equation and then iteratively updates the kernel function and its regularization parameter using the training error and the previous state of the system. The closed loop structure of the proposed algorithm increases the robustness of the technique to uncertainty and improves its convergence speed. Experimental results were generated using nine standard benchmark datasets covering a wide range of applications. Experimental results show that the proposed method generates superior or very competitive results in term of accuracy than those of classical and state-of-the-art SVM based techniques while using a significantly smaller number of support vectors.

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19

Cao, Jian Hua. "Fault Diagnosis for Electrical Control System of Automobile Based on Support Vector Machine." Applied Mechanics and Materials 666 (October 2014): 203–7. http://dx.doi.org/10.4028/www.scientific.net/amm.666.203.

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Анотація:

This paper is to present a fault diagnosis method for electrical control system of automobile based on support vector machine. We collect the common fault states of electrical control system of automobile to analyze the fault diagnosis ability of electrical control system of automobile based on support vector machine. It can be seen that the accuracy of fault diagnosis for electrical control system of automobile by support vector machine is 92.31%; and the accuracy of fault diagnosis for electrical control system of automobile by BP neural network is 80.77%. The experimental results show that the accuracy of fault diagnosis for electrical control system of automobile of support vector machine is higher than that of BP neural network.

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20

Wang, Zheng, and Mo Yong Yang. "Vector Control Study for Cascade Brushless Doubly-Fed Machine." Advanced Materials Research 433-440 (January 2012): 7247–52. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.7247.

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In this paper, the structure and principle of the cascade brushless doubly-fed machine are introduced and the mathematical model under rotor reference frame(d-q axis) is derived.The validity of the model has been verified by numerical simulation ,which provides the theoretical foundation for the study of control strategy and its implementation of this kind of machine in future.

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21

Mekrini, Zineb, Seddik Bri, Jamal Bouchnaif, and Badre Bossoufi. "Experimental results of vector control for an asynchronous machine." TELKOMNIKA (Telecommunication Computing Electronics and Control) 18, no. 6 (December 1, 2020): 3285. http://dx.doi.org/10.12928/telkomnika.v18i6.12707.

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22

Bottura, C. P., J. L. Silvino, and S. A. Augusto Filho. "H2 robust digital vector control for the induction machine." IEE Proceedings - Control Theory and Applications 143, no. 3 (May 1, 1996): 237–43. http://dx.doi.org/10.1049/ip-cta:19960122.

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23

Hammami, Rahma, Imène Ben Ameur та Khaled Jelassi. "Asynchronous machine vector control: PIα controllers for current loops". Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 234, № 1 (5 липня 2018): 107–17. http://dx.doi.org/10.1177/0959651818784211.

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Анотація:

This article deals with field-oriented control of induction machine squirrel cage. A robust fractional-order controller is applied and investigated to control the induction machine currents isd and isq. The fractional-order gives better fit in regulation operation. For this purpose, this controller form is recommended, especially in industrial systems, thanks to his flexibility, robustness and efficiency to solve complex problems such as electrical parameters changes (i.e. uncertain parameter) caused by the temperature effect. Based on frequency specification and several constraints, the fractional-order controller is designed. The fmincon toolbox optimization is used to adjust ki, kp and α values. In order to show the reliability of the developed controller in the induction machine behavior, several simulation results are carried out and illustrated.

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24

Valipour, Khalil, and Reza Najafi. "Performance Evaluation of Doubly-Fed Induction Generator Using Combined Vector Control and Direct Power Control Method." Indonesian Journal of Electrical Engineering and Computer Science 3, no. 1 (July 1, 2016): 49. http://dx.doi.org/10.11591/ijeecs.v3.i1.pp49-58.

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<p>This paper presents the performance evaluation of Doubly-Fed Induction Generator Using Combined Vector Control and Direct Power Control Method. Combined vector and direct power control (CVDPC) is used for the rotor side converter (RSC) of double-fed induction generators (DFIGs). The control system is according a direct current control by selecting suitable voltage vectors from a switching table. Actually, the proposed CVDPC encompass the benefits of vector control (VC) and direct power control (DPC) in a compact control system. Its benefits compare with VC contains rapid dynamic response, Stability against the machine parameters Changes, less computation, and naive implementation. On the other hand, it has benefits compared with DPC, contains less harmonic distortion and lower power ripple. This technique is to improve the dynamic performance of the DFIG driven by the wind-energy conversion system.</p>

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25

Gonzalez, Osvaldo, Magno Ayala, Jesus Doval-Gandoy, Jorge Rodas, Raul Gregor, and Marco Rivera. "Predictive-Fixed Switching Current Control Strategy Applied to Six-Phase Induction Machine." Energies 12, no. 12 (June 15, 2019): 2294. http://dx.doi.org/10.3390/en12122294.

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Анотація:

In applications such as multiphase motor drives, classical predictive control strategies are characterized by a variable switching frequency which adds high harmonic content and ripple in the stator currents. This paper proposes a model predictive current control adding a modulation stage based on a switching pattern with the aim of generating a fixed switching frequency. Hence, the proposed controller takes into account the prediction of the two adjacent active vectors and null vector in the ( α - β ) frame defined by space vector modulation in order to reduce the (x-y) currents according to a defined cost function at each sampling period. Both simulation and experimental tests for a six-phase induction motor drive are provided and compared to the classical predictive control to validate the feasibility of the proposed control strategy.

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26

Wong, Pak-Kin, Qingsong Xu, Chi-Man Vong, and Hang-Cheong Wong. "Rate-Dependent Hysteresis Modeling and Control of a Piezostage Using Online Support Vector Machine and Relevance Vector Machine." IEEE Transactions on Industrial Electronics 59, no. 4 (April 2012): 1988–2001. http://dx.doi.org/10.1109/tie.2011.2166235.

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27

Wan, Yi, Qi Bo Cai, and Huan Wang. "The Research on Intelligent Control Method for EHP System." Advanced Materials Research 580 (October 2012): 12–15. http://dx.doi.org/10.4028/www.scientific.net/amr.580.12.

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Анотація:

Optimized machine learning algorithm is applied to control modeling of high-speed electric-hydraulic proportional system of high nonlinear in this paper, a identification model of high-speed electric-hydraulic proportional system is built based on support vector machines, fusion intelligent method of dynamic self-adaptive internal model control and predictive control is realized for high-speed electric-hydraulic proportional control system. Internal model and inverse controller model are online adjusted together. Simulation shows the satisfactory tracking effect by intelligent technology of dynamic self-adaptive internal control and predictive control based on the support vector machine, the dynamic characteristic is greatly improved by the intelligent control strategy for high-speed electric-hydraulic proportional control system, good tracking and control effect is reached in condition of high frequency response. It provides a new intelligent control method for high-speed electric-hydraulic proportional system.

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28

Ahmadi Taleshian, Mehdi, Mahmood Ghanbari, and Seyed Mehdi Rakhtala. "Hybrid DTC strategy based on predictive control with optimization of the PI controller parameters for TPIM drives." Nexo Revista Científica 34, no. 02 (June 7, 2021): 698–709. http://dx.doi.org/10.5377/nexo.v34i02.11556.

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Анотація:

In this paper, a novel hybrid Direct Torque Control (DTC) strategy based on predictive control with optimization of the Proportional-Integral (PI) controller to improve overall performances of Three-Phase Induction Machine (TPIM) drives is proposed. The presented control technique has contained merits of the DTC method such as fast dynamic response, simple structure, less dependence to machine parameters and merits of vector control method such as high accuracy. Furthermore, a hybrid DTC method with optimal voltage vectors is presented. In the proposed control system, Genetic Algorithm (GA) is employed to obtain optimal values of the PI controller parameters. Finally, simulation results under the presented control strategy showed good performances of this method in comparison with DTC and vector control techniques.

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29

Liu, Xuanyu, and Kaiju Zhang. "Earth pressure balance control of shield tunneling machine based on nonlinear least squares support vector machine model predictive control." Measurement and Control 52, no. 1-2 (November 13, 2018): 3–10. http://dx.doi.org/10.1177/0020294018811333.

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Background: Earth pressure balance shield machines are widely used in underground engineering. To prevent ground deformation even disastrous accidents, the earth pressure in soil chamber must be kept balance to that on excavation face during shield tunneling. Therefore, in this paper an advanced control strategy that a least squares support vector machine model-based predictive control scheme for earth pressure balance is developed. Methods: A prediction model is established to predict the earth pressure in chamber during the tunneling process by means of least squares support vector machine technology. On this basis, an optimization function is given which aims at minimizing the difference between the predicted earth pressure and the desired one. To obtain the optimal control actions, an improved ant colony system algorithm is used as rolling optimization for earth pressure balance control in real time. Results: Based on the field data the simulation experiments are performed. The results demonstrate that the method proposed is very effective to control earth pressure balance, and it has good stability. Conclusion: The screw conveyor speed and advance speed are the major factors affecting the earth pressure in chamber. The excavation face could be controlled balance better by adjusting the screw conveyor speed and advance speed.

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30

Murata, T., T. Tsuchiya, and I. Takeda. "Vector control for induction machine on the application of optimal control theory." IEEE Transactions on Industrial Electronics 37, no. 4 (1990): 283–90. http://dx.doi.org/10.1109/41.103414.

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31

Zhang, Li, and Wei-Da Zhou. "Fisher-regularized support vector machine." Information Sciences 343-344 (May 2016): 79–93. http://dx.doi.org/10.1016/j.ins.2016.01.053.

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32

Saigal, Pooja, Suresh Chandra, and Reshma Rastogi. "Multi-category ternion support vector machine." Engineering Applications of Artificial Intelligence 85 (October 2019): 229–42. http://dx.doi.org/10.1016/j.engappai.2019.06.014.

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33

Luan, Tianjiao, Zhichao Wang, Yang Long, Zhen Zhang, Qi Li, Zhihao Zhu, and Chunhua Liu. "Multi-Virtual-Vector Model Predictive Current Control for Dual Three-Phase PMSM." Energies 14, no. 21 (November 3, 2021): 7292. http://dx.doi.org/10.3390/en14217292.

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Анотація:

This paper proposes a multi-virtual-vector model predictive control (MPC) for a dual three-phase permanent magnet synchronous machine (DTP-PMSM), which aims to regulate the currents in both fundamental and harmonic subspace. Apart from the fundamental α-β subspace, the harmonic subspace termed x-y is decoupled in multiphase PMSM according to vector space decomposition (VSD). Hence, the regulation of x-y currents is of paramount importance to improve control performance. In order to take into account both fundamental and harmonic subspaces, this paper presents a multi-virtual-vector model predictive control (MVV-MPC) scheme to significantly improve the steady performance without affecting the dynamic response. In this way, virtual vectors are pre-synthesized to eliminate the components in the x-y subspace and then a vector with adjustable phase and amplitude is composed of two effective virtual vectors and a zero vector. As a result, an enhanced current tracking ability is acquired due to the expanded output range of the voltage vector. Lastly, both simulation and experimental results are given to confirm the feasibility of the proposed MVV-MPC for DTP-PMSM.

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34

Grčar, Bojan, Anton Hofer, and Gorazd Štumberger. "Induction Machine Control for a Wide Range of Drive Requirements." Energies 13, no. 1 (December 31, 2019): 175. http://dx.doi.org/10.3390/en13010175.

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In this paper, a method for induction machine (IM) torque/speed tracking control derived from the 3-D non-holonomic integrator including drift terms is proposed. The proposition builds on a previous result derived in the form of a single loop non-linear state controller providing implicit rotor flux linkage vector tracking. This concept was appropriate only for piecewise constant references and assured minimal norm of the stator current vector during steady-states. The extended proposition introduces a second control loop for the rotor flux linkage vector magnitude that can be either constant, programmed, or optimized to achieve either maximum torque per amp ratio or high dynamic response. It should be emphasized that the same structure of the controller can be used either for torque control or for speed control. Additionally, it turns out that the proposed controller can be easily adapted to meet different objectives posed on the drive system. The introduced control concept assures stability of the closed loop system and significantly improves tracking performance for bounded but arbitrary torque/speed references. Moreover, the singularity problem near zero rotor flux linkage vector length is easily avoided. The presented analyses include nonlinear effects due to magnetic saturation. The overall IM control scheme includes cascaded high-gain current controllers based on measured electrical and mechanical quantities together with a rotor flux linkage vector estimator. Simulation and experimental results illustrate the main characteristics of the proposed control.

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Yifan Zhao and T. A. Lipo. "Space vector PWM control of dual three-phase induction machine using vector space decomposition." IEEE Transactions on Industry Applications 31, no. 5 (1995): 1100–1109. http://dx.doi.org/10.1109/28.464525.

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Chen, Wen Zhuo, Xiao Yu Zhang, and Xiao Mei Sui. "Simulation of Permanent Magnet Synchronous Motor Field Oriented Vector Control System." Applied Mechanics and Materials 672-674 (October 2014): 1234–37. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1234.

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This template illustrates the control system of permanent magnet synchronous motor(PMSM) which uses field oriented vector control(field oriented vector control). PMSM is a complex, strong coupling and nonlinear system. And field oriented vector control could provide good performance as well as the PI controller setted with well parameter matching. Whereas limited by the number of voltage vector, the other control method of PMSM, direct torque control, could not satisfy accurate control when the machine running with a low speed. So modulation of the whole system is built here to realize closed-loop field oriented vector control control by keeping id=0 , and the machine model and the transformation among different coordinate system are discussed. The system is verified effective and feasible.

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Javaid, Momna, Muhammad Shahzad Sarfraz, Muhammad Umar Aftab, Qamar uz Zaman, Hafiz Tayyab Rauf, and Khalid A. Alnowibet. "WebGIS-Based Real-Time Surveillance and Response System for Vector-Borne Infectious Diseases." International Journal of Environmental Research and Public Health 20, no. 4 (February 20, 2023): 3740. http://dx.doi.org/10.3390/ijerph20043740.

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The diseases transmitted through vectors such as mosquitoes are named vector-borne diseases (VBDs), such as malaria, dengue, and leishmaniasis. Malaria spreads by a vector named Anopheles mosquitos. Dengue is transmitted through the bite of the female vector Aedes aegypti or Aedes albopictus mosquito. The female Phlebotomine sandfly is the vector that transmits leishmaniasis. The best way to control VBDs is to identify breeding sites for their vectors. This can be efficiently accomplished by the Geographical Information System (GIS). The objective was to find the relation between climatic factors (temperature, humidity, and precipitation) to identify breeding sites for these vectors. Our data contained imbalance classes, so data oversampling of different sizes was created. The machine learning models used were Light Gradient Boosting Machine, Random Forest, Decision Tree, Support Vector Machine, and Multi-Layer Perceptron for model training. Their results were compared and analyzed to select the best model for disease prediction in Punjab, Pakistan. Random Forest was the selected model with 93.97% accuracy. Accuracy was measured using an F score, precision, or recall. Temperature, precipitation, and specific humidity significantly affect the spread of dengue, malaria, and leishmaniasis. A user-friendly web-based GIS platform was also developed for concerned citizens and policymakers.

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Zhang, Ru Quan, Jian Qiang Li, Yu He, and Hui Jiang. "Prediction of Yarn Quality by Support Vector Machine." Advanced Materials Research 503-504 (April 2012): 1429–32. http://dx.doi.org/10.4028/www.scientific.net/amr.503-504.1429.

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For the prediction of yarn quality, this paper presents method to predict the quality of the spinning by a support vector machine. The input parameters to support vector machines including density of coarse yarn, roving twist factor, yarn linear density, yarn twist factor , the output variable is the CV values of spinning, breaking strength, establishment prediction model of CV values, breaking strength SVM. The results showed that: 11 groups of training samples randomly selected from 13 groups samples, two groups as predict sample, forecast errors are below 5% with high accuracy. This research provides a new approach for the spinning process design and quality control.

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Hasoun, Mhammed, Aziz El Afia, Mohamed Khafallah, and Karim Benkirane. "Experimental implementation PWM strategy for dual three-phase PMSM using 12-sector vector space decomposition applied on electric ship propulsion." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 4 (December 1, 2020): 1701. http://dx.doi.org/10.11591/ijpeds.v11.i4.pp1701-1710.

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The current paper aims at presenting and examining an implementation on a digital signal processor (DSP) of the conventional space vector pulse width modulation (CSVPWM) so as to control the dual three phase permanent magnet synchronous motors (DTP-PMSM) drives applied on electric ship propulsion. It is also an attempt to accomplish a developed control of this technique based on vector space decomposition (VSD) strategy. By this strategy, the analysis and the control of the machine are achieved in three two-dimensional orthogonal subspaces. Among the 12 voltage vectors having maximum, the conventional technique namely the adjacent two-vectors (12SA2V) is chosen. Thereby, the test platform allows the implementation of the chosen vectors which are modeled on MATLAB/Simulink using block diagrams and the automatically generated code which is targeted in the DSP card processor. Simulation and experimental results have exposed the efficiency of the proposed test bench of 5 KW prototype machine by using a low-cost TMS32F28379D.

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Vasu. R, Ramana, George Fernandez S., and Vijayakumar K. "Enhanced space vector modulated scalar control of induction motor." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 2 (February 1, 2021): 707. http://dx.doi.org/10.11591/ijeecs.v21.i2.pp707-713.

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<p>A conventional vector control of the asynchronous machine makes an analogy of an equivalent separately excited DC machine. It offers a decoupled control of torque and flux which is perpendicular to each other hence one vector is not interfered by other parameters. So, torque and speed control is achieved in an isolated manner even though they are closely interlinked. This is implemented by aligning the rotor flux with the direct axis of the synchronously rotating reference frame. PI controllers play a key role to achieve the desired topology of the VFD. Three controllers are used in the system, flux, speed and torque controller. Tuning of flux controller is quite simple, but in case of speed and torque, it became quite tricky because the output of the speed controller is the reference signal of torque controller. Moreover, there is no distinct method to tune the controllers in the vector control system. Still, the entire high-performance dynamic response of the machine depends on the perfect tuning of those controllers. From the above analysis, it is understood that system identification is essential to tune the PI controllers. But being an asynchronous machine, to obtain system transfer function in a decoupled manner is very difficult. To overcome this problem, the proposed model will be Conventional sine PWM modulated switching pulses are used to implement variable frequency drives for induction motor. Space vector modulated PWM switching pulse is used to fire IGBT. In the case of sine, PWM modulated switching; DC bus voltage utilization is 50% whereas in space vector modulated inverter 57.73% DC Bus voltage utilization can be achieved. <strong></strong></p>

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Całuch, Artur, Adam Cieślikowski, and Małgorzata Plechawska-Wójcik. "Application of support vector machine in a traffic lights control." Journal of Computer Sciences Institute 14 (March 30, 2020): 37–42. http://dx.doi.org/10.35784/jcsi.1573.

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This article presents the process of adapting support vector machine model’s parameters used for studying the effect of traffic light cycle length parameter’s value on traffic quality. The survey is carried out using data collected during running simulations in author’s traffic simulator. The article shows results of searching for optimum traffic light cycle length parameter’s value.

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Burdilna, Evgeniia, Sergii Serhiienko, and Oleksiy Chornyi. "Vector control system of electric drive of grain machine conveyor." Electrical Engineering and Power Engineering, no. 2 (June 30, 2021): 8–16. http://dx.doi.org/10.15588/1607-6761-2021-2-1.

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Purpose. Synthesis of an automatic control system for an asynchronous electric drive of a grain thrower conveyor based on a frequency converter with vector control. Methodology. The research was carried out using methods of mathematical modeling of an electric drive; using methods of tuning optimization and regulator synthesis. The technique of synthesis of vector control systems is based on the representation of a non-stationary multi-connected object, which is an AC machine, in the form of a set of stationary subobjects with linear links in the main control channels. Findings. The study of the work of the subordinate regulation system, which implements the principles of vector control, oriented along the vector of the rotor flux linkage, has been carried out. The modeling of the processes of AM excitation, AM start-up at idle speed, nominal load surge, speed reduction has been carried out. It was found that the synthesized system is characterized by good quality indicators. The overshoot at start does not exceed 5%, the regulation time is 0.4 s, the torque limitation is carried out at a predetermined level. It has been proven that oscillatory processes in transient modes with significant torque surges with classical settings of loop regulators can be compensated by introducing artificial cross-links into the control part of the electric drive. Originality. A system of subordinate regulation of the blood pressure of the grain thrower trimmer conveyor has been implemented to set the speed of the grain flow with the aim of throwing grain at a given distance by creating an appropriate ballistic flight trajectory, which ensures a reduction in losses from damage to grain. Practical value. The structure of the vector control system of a frequency-controlled asynchronous electric drive with additional compensating cross-connections between active and reactive energy control channels is proposed to improve the quality indicators of the system.

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孙, 静. "Process Control of Mixed Data Based on Support Vector Machine." Dynamical Systems and Control 11, no. 01 (2022): 1–10. http://dx.doi.org/10.12677/dsc.2022.111001.

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Qi, Xin, Chang Song Wang, and Xiang Hua Ma. "Sensorless Vector Control of Induction Motor Based on Machine Model." Advanced Materials Research 572 (October 2012): 371–75. http://dx.doi.org/10.4028/www.scientific.net/amr.572.371.

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Spatial orientation and magnitude of the rotor flux is essential for vector control of induction motor. Traditionally, current model serves for rotor flux estimation and rotor must be measured by speed sensor. Due to advantages of low cost and high reliability, control the induction motor without sensor draws great attention of scholars around the world. Closed-loop observers or open-loop estimators are used for such purpose. In this paper a new method of sensorless vector control of induction motor is proposed and simulation is implemented to verify the scheme.

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45

Sharaf-Eldin, T., M. W. Dunnigan, J. E. Fletcher, and B. W. Williams. "Nonlinear robust control of a vector-controlled synchronous reluctance machine." IEEE Transactions on Power Electronics 14, no. 6 (November 1999): 1111–21. http://dx.doi.org/10.1109/63.803405.

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Feng, Yong, Yun-jian Ge, Hui-bin Cao, and Yu-xiang Sun. "Learning control of nonhonolomic robot based on support vector machine." Journal of Central South University 19, no. 12 (December 2012): 3400–3406. http://dx.doi.org/10.1007/s11771-012-1421-7.

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47

Bueno, A. A., J. M. Aller, M. I. Gimenez, V. M. Guzman, and J. A. Restreop. "Induction Machine Estimator for Vector Control Applications Using Neural Networks." IEEE Power Engineering Review 18, no. 8 (August 1998): 50–52. http://dx.doi.org/10.1109/39.691718.

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Joshi, Bhakti M., and Mukul C. Chandorkar. "Vector Control of Two-motor Single-inverter Induction Machine Drives." Electric Power Components and Systems 42, no. 11 (July 30, 2014): 1158–71. http://dx.doi.org/10.1080/15325008.2014.921949.

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Klyuyev, О., A. Sadovoi, and Y. Sokhina. "CONSTRUCTION OF ROTOR ANGLE IDENTIFIER IN VECTOR CONTROL SYSTEMS OF DOUBLE FEED MACHINES." Collection of scholarly papers of Dniprovsk State Technical University (Technical Sciences) 2, no. 39 (December 21, 2021): 74–81. http://dx.doi.org/10.31319/2519-2884.39.2021.9.

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In asynchronous electric drives with vector control on the rotor, it is necessary to calculate the value of the sine and cosine of the angle of rotation of the rotor relative to the stator to form control actions. When using angle sensors, complex structural tasks can arise — placement and reliable mounting of the sensor on the shaft and, accordingly, the task of the overall layout of the unit. For high-power machines, the tasks of developing and creating the design of the sensor itself arise. If serial rotor angular position sensors can be used, the task of placing and mounting the sensor is no less difficult. In these cases it is necessary to deduce the second end of a shaft from the case of the engine with contact rings that complicates its design. Therefore, the urgent need to create more reliable electric drives with vector control systems on the rotor is the synthesis of identifiers of the angle of rotation of the rotor. Identifiers are known whose calculation algorithms are based on determining the projections of the flow coupling vectors. In the work with the use of coordinate transducers of projections of stator or rotor current vectors and equations of electromagnetic circuits of an asynchronous machine, the synthesis and subsequent analysis of the properties of the rotor position angle identifier in vector control systems of dual power machines is performed. New equations of the identifier of flux couplings are received, its stability is investigated and on conditions of stability types of electric drives in which it is possible to apply the offered identifier are defined. The stability of the vector control system and sufficient identification accuracy when using the proposed equations and functions are confirmed by the method of mathematical modeling of the recommended electric drive systems in different operating modes.

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Serra, João, Imed Jlassi, and Antonio J. Marques Cardoso. "A Computationally Efficient Model Predictive Control of Six-Phase Induction Machines Based on Deadbeat Control." Machines 9, no. 12 (November 23, 2021): 306. http://dx.doi.org/10.3390/machines9120306.

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Model predictive current control (MPCC) has recently become a viable alternative for multiphase electric drives, because it easily exploits the inherent advantages of multi-phase machines. However, the prediction in MPCC requires a high number of voltage vectors (VVs), being therefore computationally demanding. In that regard, this paper proposes a computationally efficient MPCC of an asymmetrical six-phase induction machine drive (ASIMD) that reduces the number of VVs used for prediction. By using the characteristics of the deadbeat control (DB), the proposed method obtains a reference voltage vector (RVV), where its position will serve as a reference and integrates the MPCC scheme. Only 4 out of 13 predictions are needed to determine the best VV, dramatically reducing the algorithm computation. Experimental results for a six-phase case study compare the standard MPCC with the suggested method, confirming that deadbeat model predictive current control (DB-MPCC) shows that the execution time can be shortened by 48.8% and successfully improve the motor performance and efficiency.

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