Sentsov E.V., Meshcheryakov V.N. Neural Network Speed Observer Development to Improve the Dynamic Stability of a Sensorless Vector Control System

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Abstract

The paper considers the problem of the speed observer indication influence on the vector control system of an asynchronous motor. The classification of applied sensorless control methods is given. The analysis of advantages and disadvantages of the most common structures for constructing velocity observers is carried out. Mathematical models of individual observers were developed and created in the Matlab Simulink software package. The work of the obtained models was tested in various modes, data on the drive dynamics were obtained. Conclusions are drawn about the work of observers based on the classical mathematical apparatus in situations associated with the change in any parameters of the controlled object. The concept of neural networks is considered as a tool capable of leveling the shortcomings of classical observers. The analysis of neurostructures suitable for control tasks of complex dynamic objects has been carried out. An element of the Neural Network Toolbox (Deep Learning Toolbox) library, Predictive Controller, was used as a neuroregulator. A model was built using the neurostructure as an observer. The process of data integration and adjustment of neural network parameters is described in detail. A study of the obtained control system behavior in dynamic modes was carried out. Also, the vector control system behavior, an adaptation mechanism was developed that takes into account the advantages and disadvantages of 2 different approaches to the implementation of velocity determination to create a model with a combined observer structure. A model with a combined observer structure based on a neural network and a classical observer is obtained. The behavior of the resulting control system in various simulation modes has been studied.

Keywords

simulation, variable speed drive, control system, vector control, asynchronous motor, Predictive controller, observers, sensorless vector control, learning, neural networks.

Evgeny V. Sentsov Postgraduate Student, Electric Drive Department, Lipetsk State Technical University, Lipetsk, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0002-8383-5139

Victor N. Meshcheryakov D.Sc. (Engineering), Professor, Head of the Electric Drive Department, Electric Drive Department, Lipetsk State Technical University, Lipetsk, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., https://orcid.org/0000-0003-0984-5133

 
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Sentsov E.V., Meshcheryakov V.N. Neural Network Speed Observer Development to Improve the Dynamic Stability of a Sensorless Vector Control System. Elektrotekhnicheskie sistemy i kompleksy [Electrotechnical Systems and Complexes], 2022, no. 2(55), pp. 18-24. (In Russian). https://doi.org/10.18503/2311-8318-2022-2(55)-18-24

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