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Identification of Friction Parameters Based on Genetic Algorithm in Servo Control System

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Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7002))

Abstract

The friction is detrimental to the normal work of the servo system, but the friction mechanism is very complicated. In this paper, Tustin friction model is used as the friction parameter identification, reflecting the phenomenon of friction in the system, and laying the foundation for the friction compensation. Tustin model is a nonlinear friction one, and the friction properties can be reflected better with four friction parameters. In this paper, we use genetic algorithms for parameter identification of these parameters, and its search capabilities and more robust than traditional algorithms, to be more accurate recognition results.

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References

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, JinZhong University, JinZhong, China

    Lifen Wu

Authors
  1. Lifen Wu
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Wu, L. (2011). Identification of Friction Parameters Based on Genetic Algorithm in Servo Control System. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7002. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23881-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-23881-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23880-2

  • Online ISBN: 978-3-642-23881-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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