Preview

Power engineering: research, equipment, technology

Advanced search

Optimized sensorless control systems for cargo movement mechanisms

https://doi.org/10.30724/1998-9903-2021-23-6-87-98

Abstract

THE PURPOSE. Investigation of the control system of the cargo movement mechanism when using different variants of sensorless control. The search for the optimal option, in which the formation of the speed is identical to the data obtained from the speed sensor. Analysis of the results obtained during the study, including the results obtained taking into account the heating of the motor windings.

METHODS. The tasks set during the research are implemented by simulation modeling using the Matlab Simulink computer simulation environment.

RESULTS. The article considers systems with different types of velocity observers. A system is implemented that takes into account the heating of the stator and rotor windings of an asynchronous motor, in which a non-adaptive observer and different types of neural network controller were introduced. A combined method of using neural network regulators is proposed.

CONCLUSION. Sensorless control systems are relevant for use in industries with the presence, according to the conditions of the technological process, of high temperatures. The conducted research has shown that the use of neural network technologies allows you to work with settings of different levels and types. The proposed method, implying the use of joint work of neural network observers with various neurostructures, allows for speed testing in the entire range. The connection with cloud storage present in the proposed structure leads to the unloading of the management system, allowing to increase the process of analyzing data coming from the object.

About the Authors

A. V. Sinyukov
Lipetsk State Technical University
Russian Federation

 Lipetsk 



T. V. Sinyukova
Lipetsk State Technical University
Russian Federation

 Lipetsk 



E. I. Gracheva
Kazan State Power Engineering University
Russian Federation

 Kazan



M. Kolcun
Technical University of Kosice
Slovakia

 Bratislava 



S. Valtchev
New University of Lisbon
Bulgaria

Sofia 



References

1. Sokolovsky GG. Alternating current electric drives with frequency control. M.: Academy. 2006. 265 p.

2. Firago BI, Alexandrovsky SV. Fananana, ny toetra sy ny masontsivana ny synchronous maotera amin'ny maharitra lasibatry ao vector sy scalar matetika fanaraha-maso. Angovo. Fitsarana ambony toeram-pampianarana sy ny hery-ny fikambanana ny CIS. 2019;62(3):205-218.

3. Shayakhmetova LV, Kharitonov VL. Stabilization of a scalar equation with delay in the state and control variables. Vestnik of saint Petersburg University. Applied Mathematics. Computer Science. Control Processes. 2014;4:144-150.

4. Meshcheryakov V, Sinyukova T, Sinyukov A, et al. Analysis of the effectiveness of using the block for limiting the vibrations of the load on the mechanism of movement of the bogie with various control systems. E3S Web of Conferences. Sustainable Energy Systems: Innovative Perspectives (SES-2020), Saint-Petersburg, Russia, 2020, 220, 01059, October 29-30.

5. Meshcheryakov V, Sinykova T, Sinyukov A,et al. Modeling and analysis of vector control systems for asynchronous motor. High Speed Turbomachines and Electrical Dreves Conference 2020 (HSTED-2020), Prague, Czech Republic.

6. Dadenkov DA, Solotskii EM, Shachkov AM. Modelirovanie sistemy vektornogo upravleniya asinkhronnym dvigatelem v pakete Matlab/Simulink. Vestnik Permskogo natsional'nogo issledovatel'skogo universitete. Elektrotekhnika, informatsionnye tekhnologii, sistemy upravleniya. 20183;11:117-128.

7. Chunyun Fu, Minghui Hu. Adaptive sliding mode-based direct yaw moment control for electric vehicles. 2015 International Conference on Control, Automation and Information Sciences (ICCAIS). Changshu, China, 2015, 15634631, October 29-31.

8. Sayali S. Patil, Vijayraj Wanaskar, PD. Shendge, et al. Sliding Mode and Inertial Delay Based Direct Yaw Moment Control for AGVs. 2021 6th International Conference for Convergence in Technology (I2CT), Maharashtra, India. 20593534. (2-4 April 2021).

9. Sinyukov AV, Sinyukova TV. Observers of the state in control systems of an electric drive with an asynchronous motor. Control systems of electrotechnical objects (SUETO-8): proceedings of the eighth All-Russian Scientific and practical conference, Tula. 2018. pp. 64-66.

10. Ostrovlyanchik VYu. Popolzen IYu. Asynchronous motor model for sensorless information and control systems of automated electric drive. Bulletin of the Kuzbass State Technical Un1 (113). pp. 111-120.

11. Gracheva YI, Chernova NV, Fedotov AI, Fedotov EA. Local Fourier transformation application for mathematic modeling of synchronous machine valve actuator. Journal of engineering and applied sciences. 2016;11(1):2939-2945.

12. Mairaj Ali, Muwahida Liaquat. Comparison Between Distributed Observer And Adaptive Distributed Observer. 2018 8th International Conference on Electronics Information and Emergency Communication (ICEIEC). Maharashtra, India. 2018. 18132759 (15-17 June).

13. Mikhail P. Belov, Nguyen Van Lanh, Tran Dang Khoa. State Observer based Elman Recurrent Neural Network for Electric Drive of Optical-Mechanical Complexes. 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus). 2021. St. Petersburg, Moscow, Russia. 20553530. (26-29 January).

14. Hu Z, Bodyanskiy YV, Tyshchenko OK, A Multidimensional Adaptive Growing Neuro-Fuzzy System and Its Online Learning Procedure. Advances in Intelligent System and Computing. 689, 2018;689:186-203.

15. Sklyar AV, Chizhma SN, Chegodaev FV. Sensorless control of the rotor speed of an asynchronous motor. News of higher educational institutions. Electromechanics. 2017;60(1):14-19.


Review

For citations:


Sinyukov A.V., Sinyukova T.V., Gracheva E.I., Kolcun M., Valtchev S. Optimized sensorless control systems for cargo movement mechanisms. Power engineering: research, equipment, technology. 2021;23(6):87-98. (In Russ.) https://doi.org/10.30724/1998-9903-2021-23-6-87-98

Views: 250


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1998-9903 (Print)
ISSN 2658-5456 (Online)