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Adaptive Control for Induction Servo Motor Based on Wavelet Neural Networks

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3174))

Abstract

This paper presents an adaptive control system using wavelet neural networks (WNN) for an induction servo drive motor with complex of non-linear, multivariable, strong coupling, slow time-varying properties, etc., and many uncertainties such as mechanical parametric variation and external disturbance. The motivation of developing a new method is to overcome the limitation of conventional control methods which depends on the accurate model and cannot guarantee satisfactory control performance. The proposed scheme with on-line learning has the good tracking and dynamic performance, the ability of adaptive learning from the process and good robustness to uncertainties. Simulation results demonstrate the effectiveness of the proposed method.

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References

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© 2004 Springer-Verlag Berlin Heidelberg

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Wu, Q., Liu, Y., Zhang, D., Zhang, Y. (2004). Adaptive Control for Induction Servo Motor Based on Wavelet Neural Networks. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_24

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  • DOI: https://doi.org/10.1007/978-3-540-28648-6_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22843-1

  • Online ISBN: 978-3-540-28648-6

  • eBook Packages: Springer Book Archive

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