scholarly journals CONSTRUCTION OF ROTOR ANGLE IDENTIFIER IN VECTOR CONTROL SYSTEMS OF DOUBLE FEED MACHINES

2021 ◽  
Vol 2 (39) ◽  
pp. 74-81
Author(s):  
О. Klyuyev ◽  
A. Sadovoi ◽  
Y. Sokhina
Keyword(s):  
Vector Control ◽  
Control Systems ◽  
Angular Position ◽  
Position Angle ◽  
Identification Accuracy ◽  
Electric Drives ◽  
Operating Modes ◽  
Complex Structural ◽  
Conditions Of Stability ◽  
Angle Of Rotation

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.

scholarly journals Improving the energy efficiency of electric drives for auxiliary units of traction rolling stock

2021 ◽  
Vol 2131 (4) ◽  
pp. 042085
Author(s):  
T S Titova ◽  
A M Evstaf’ev ◽  
A A Pugachev
Keyword(s):  
Energy Efficiency ◽  
Control Systems ◽  
Induction Motor ◽  
Induction Machine ◽  
Rolling Stock ◽  
Electric Drives ◽  
Operating Modes ◽  
Stator Current ◽  
Power Loss Reduction ◽  
Rotor Winding

Abstract The review of technical solutions and schematic characteristics of auxiliary drives for traction vehicles has shown that the most rational variant is an electric drive with an induction machine. Given the operating modes of the auxiliary drives and the share of their power consumption in the total locomotive power, the task of using scalar control systems for induction machines becomes relevant. Based on a mathematical model describing the dynamic energy conversion processes in the T-shape substitution circuit of an induction motor, taking into account stator steel losses and current displacement effects in the rotor winding and saturation along the main magnetic path, possibilities for reducing stator current have been investigated. In order to improve the energy efficiency of electric drives two variants of control system have been proposed. One based on search method of self-tuning to the stator current minimum and the other - on maintaining the power factor of induction motor at the level that ensures equality of active and reactive components of stator current. The hardware and software requirements for implementing control systems have been analysed. Modelling using Matlab has shown that both control systems work - power loss reduction can be as low as 50% and as high as 60% in certain modes.

scholarly journals Unknown SAR Target Identification Method Based on Feature Extraction Network and KLD–RPA Joint Discrimination

2021 ◽  
Vol 13 (15) ◽  
pp. 2901
Author(s):  
Zhiqiang Zeng ◽  
Jinping Sun ◽  
Congan Xu ◽  
Haiyang Wang
Keyword(s):  
Feature Extraction ◽  
Position Angle ◽  
Automatic Target Recognition ◽  
Identification Accuracy ◽  
Training Dataset ◽  
Target Feature ◽  
Practical Applications ◽  
Feature Vectors ◽  
Identification Method ◽  
Leibler Divergence

Recently, deep learning (DL) has been successfully applied in automatic target recognition (ATR) tasks of synthetic aperture radar (SAR) images. However, limited by the lack of SAR image target datasets and the high cost of labeling, these existing DL based approaches can only accurately recognize the target in the training dataset. Therefore, high precision identification of unknown SAR targets in practical applications is one of the important capabilities that the SAR–ATR system should equip. To this end, we propose a novel DL based identification method for unknown SAR targets with joint discrimination. First of all, the feature extraction network (FEN) trained on a limited dataset is used to extract the SAR target features, and then the unknown targets are roughly identified from the known targets by computing the Kullback–Leibler divergence (KLD) of the target feature vectors. For the targets that cannot be distinguished by KLD, their feature vectors perform t-distributed stochastic neighbor embedding (t-SNE) dimensionality reduction processing to calculate the relative position angle (RPA). Finally, the known and unknown targets are finely identified based on RPA. Experimental results conducted on the MSTAR dataset demonstrate that the proposed method can achieve higher identification accuracy of unknown SAR targets than existing methods while maintaining high recognition accuracy of known targets.

scholarly journals Synthesis of vector control systems by localization method

2019 ◽  
Vol 1333 ◽  
pp. 042017
Author(s):  
E S Kucher ◽  
N S Popov ◽  
T V Gryzunova
Keyword(s):  
Vector Control ◽  
Control Systems ◽  
Localization Method

Efficiency Increasing of Traction Electric Drives with Induction Motors and Vector Control System

2021 ◽  
Vol 92 (9) ◽  
pp. 476-480
Author(s):  
Yu. M. Inkov ◽  
A. S. Kosmodamianskiy ◽  
A. A. Pugachev ◽  
S. V. Morozov
Keyword(s):  
Control System ◽  
Vector Control ◽  
Induction Motors ◽  
Electric Drives ◽  
Vector Control System

scholarly journals Motions models of a two-wheeled experimental sample

2021 ◽  
pp. 40-49
Author(s):  
Anatoliy Kulik ◽  
Konstantin Dergachov ◽  
Sergey Pasichnik ◽  
Sergey Yashyn
Keyword(s):  
Automatic Control ◽  
State Space ◽  
Experimental Model ◽  
Functional Properties ◽  
Angular Position ◽  
The Body ◽  
Angular Motion ◽  
Physical Models ◽  
Experimental Sample ◽  
Electric Drives

The subject of study is the physical processes of translational and angular motion of a two-wheeled experimental sample. The goal is to develop physical, mathematical, and graphic models of the translational and angular motions of a two-wheeled experimental sample as an object of automatic control. The objectives: to form physical models of a two-wheeled experimental sample; to develop a nonlinear mathematical description of the processes of translational and angular sample`s motions using the Lagrange approach; to obtain a linearized mathematical sample`s description as an object of automatic control in the state space and frequency domain; to generate graphic models in the form of structural diagrams in the time and frequency domains; to analyze the functional properties of an object of automatic control: stability, controllability, observability, structural and signal diagnosability concerning violations of the functional properties of electric drives and sensors of the angular position of the body and wheels. The methods of the study: the Lagrange method, Taylor series, state-space method, Laplace transformations, Lyapunov, Kalman criteria, and diagnosability criterion. The results: physical models of a two-wheeled experimental sample have been obtained in the form of a kinematic diagram of the mechanical part and the electric circuit of an electric drive; mathematical descriptions of translational and angular motions have been developed in nonlinear and linearized forms; structural diagrams have been developed; functional characteristics of a two-wheeled experimental model as an object of automatic control have been analyzed to solve problems of control algorithms synthesis. Conclusions. The scientific novelty lies in obtaining new models that describe the translational and angular motion of a two-wheeled experimental model as an object of automatic control. The obtained models differ from the known ones by considering the dynamic properties of sensors and electric drives, as well as the relationship of movements.

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