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Modified NFTSM on State in Switched Reluctance Motor Speed Controller

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8032))

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Abstract

In switched reluctant motor driving system(SRD) , accurate controlling speed was important. In the paper, a nonsingular fast terminal sliding mode controller based on states (NFTSM-S) was proposed with judging convergent states, which combined linear sliding mode controller with nonsingular terminal sliding mode with state. NFTSM-S reduced convergent time and ripple of system output, in which state parameters was accurate at convergent state. The simulation results show it is a valid to switched reluctant motor speed tracing control with faster speed response.

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References

  1. Feng, Y., Yu, X.H., Man, Z.H.: Non-singular terminal sliding mode control of rigid manipulators. Automatica 38, 2159–2167 (2002)

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  2. Yu, X.H., Man, Z.H.: Fast terminal sliding-mode control design for nonlinear dynamical systems. IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications 49, 261–264 (2002)

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  3. Robert, B.I., Rik, W.D.D.: Direct instantaneous torque control of switched reluctance drives. In: IEEE 37th IAS Annual Meeting, pp. 1605–1609 (2002)

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Author information

Authors and Affiliations

  1. School of Electrical and Control Engineering, Xi’an University of Science and Technology, 710054, Xi’an, China

    Yong Cheng

Authors
  1. Yong Cheng
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Editor information

Editors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, 37 Xueyuan Road, 100191, Beijing, China

    Zengchang Qin

  2. School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai Nomi, 923-1292, Ishikawa, Japan

    Van-Nam Huynh

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© 2013 Springer-Verlag Berlin Heidelberg

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Cheng, Y. (2013). Modified NFTSM on State in Switched Reluctance Motor Speed Controller. In: Qin, Z., Huynh, VN. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2013. Lecture Notes in Computer Science(), vol 8032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39515-4_18

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  • DOI: https://doi.org/10.1007/978-3-642-39515-4_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39514-7

  • Online ISBN: 978-3-642-39515-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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