Computer visualization of optimality criterion’s weighting coefficients of electromechanical system | Научно-инновационный портал СФУ

Computer visualization of optimality criterion’s weighting coefficients of electromechanical system

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: Computer Science On-line Conference, CSOC 2020

Год издания: 2020

Идентификатор DOI: 10.1007/978-3-030-51974-2_17

Ключевые слова: automated electric drive, optimal control algorithms, optimality criterion’s weighting coefficients, tools for computer visualization

Аннотация: Computer visualization of optimality criterion’s weighting coefficients is solved by modelling tools of MATLAB SIMULINK. The excavator’s AC drive is studied as an electromechanical system. Thus the actual practical problem is studied – improvement of mining excavator’s rotary drive performance. Asset target is designed by differential equations. Optimality criterion is measured as a result of minimization of squared deviation location and controlled impacts. Algorithm of optimal control is presented according to Pontryagin’s maximum theory. Choosing of weighting coefficients resides into finding the intersection of the permissible values surfaces of the elastic moment and the possible values of the gap in the mechanical part of the rotary mechanism’s electric drive during the transition process. The time of the transition process is directly related to the performance of the excavator, and the nature of the transition process - with the safety of the equipment. The nature of the transition process depends on the dynamic loads determined by the gap in the tooth zone of the rotation mechanism at the initial moments of rotation. Computer visualization of the weighting factor selection process as a result of using MATLAB SIMULINK tools was demonstrated. This method of choosing the optimality criterion coefficients helps to reduce the maximum value of the elastic moment throws while reducing the time of the transition process by taking into account the operating conditions of a particular excavator. #CSOC1120 © Springer Nature Switzerland AG 2020.

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Издание

Журнал: Advances in Intelligent Systems and Computing

Выпуск журнала: Vol. 1226 AISC

Номера страниц: 201-209

ISSN журнала: 21945357

Персоны

  • Kurochkin N.S. (Khakass Technical Institute – Branch of the Siberian Federal University, Shchetinkina str. 27, Abakan, 655017, Russian Federation)
  • Kochetkov V.P. (Khakass Technical Institute – Branch of the Siberian Federal University, Shchetinkina str. 27, Abakan, 655017, Russian Federation)
  • Kochetkov M.V. (Norilsk State Industrial Institute, 50 years of October str. 7, Norilsk, 663310, Russian Federation)
  • Noskov M.F. (Sayano-Shushensky Branch of the Siberian Federal University, Svobodnyi str. 79, Krasnoyarsk, 660074, Russian Federation)
  • Kolovsky A.V. (Khakass Technical Institute – Branch of the Siberian Federal University, Shchetinkina str. 27, Abakan, 655017, Russian Federation)

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