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Application of Genetic Algorithm Elements to Modelling of Rotation Processes in Motion Transmission Including a Long Shaft

Author

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  • Andriy Chaban

    (Faculty of Transport, Electrical Engineering and Computer Science, Kazimierz Pulaski University of Technology and Humanities, Malczewskiego 29, 26-600 Radom, Poland)

  • Marek Lis

    (Faculty of Electrical Engineering, Czestochowa University of Technology, Al. Armii Krajowej 17, 42-201 Czestochowa, Poland)

  • Andrzej Szafraniec

    (Faculty of Transport, Electrical Engineering and Computer Science, Kazimierz Pulaski University of Technology and Humanities, Malczewskiego 29, 26-600 Radom, Poland)

  • Radoslaw Jedynak

    (Faculty of Transport, Electrical Engineering and Computer Science, Kazimierz Pulaski University of Technology and Humanities, Malczewskiego 29, 26-600 Radom, Poland)

Abstract

Genetic algorithms are used to parameter identification of the model of oscillatory processes in complicated motion transmission of electric drives containing long elastic shafts as systems of distributed mechanical parameters. Shaft equations are generated on the basis of a modified Hamilton–Ostrogradski principle, which serves as the foundation to analyse the lumped parameter system and distributed parameter system. They serve to compute basic functions of analytical mechanics of velocity continuum and rotational angles of shaft elements. It is demonstrated that the application of the distributed parameter method to multi-mass rotational systems, that contain long elastic elements and complicated control systems, is not always possible. The genetic algorithm is applied to determine the coefficients of approximation the system of Rotational Transmission with Elastic Shaft by equivalent differential equations. The fitness function is determined as least-square error. The obtained results confirm that application of the genetic algorithms allow one to replace the use of a complicated distributed parameter model of mechanical system by a considerably simpler model, and to eliminate sophisticated calculation procedures and identification of boundary conditions for wave motion equations of long elastic elements.

Suggested Citation

  • Andriy Chaban & Marek Lis & Andrzej Szafraniec & Radoslaw Jedynak, 2020. "Application of Genetic Algorithm Elements to Modelling of Rotation Processes in Motion Transmission Including a Long Shaft," Energies, MDPI, vol. 14(1), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:14:y:2020:i:1:p:115-:d:469507
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    References listed on IDEAS

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    1. Chwastek, Krzysztof & Szczyglowski, Jan, 2006. "Identification of a hysteresis model parameters with genetic algorithms," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 71(3), pages 206-211.
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    4. Wei Chen & Jiaojiao Liang & Tingna Shi, 2018. "Speed Synchronous Control of Multiple Permanent Magnet Synchronous Motors Based on an Improved Cross-Coupling Structure," Energies, MDPI, vol. 11(2), pages 1-16, January.
    5. Xianglin Li & K. T. Chau & Yubin Wang, 2016. "Modeling of a Field-Modulated Permanent-Magnet Machine," Energies, MDPI, vol. 9(12), pages 1-15, December.
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    Cited by:

    1. Jacek Kabziński & Przemysław Mosiołek, 2021. "Integrated, Multi-Approach, Adaptive Control of Two-Mass Drive with Nonlinear Damping and Stiffness," Energies, MDPI, vol. 14(17), pages 1-23, September.

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