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Fast nonsingular terminal sliding mode control for permanent-magnet linear motor via ELM

  • Extreme Learning Machine and Deep Learning Networks
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Abstract

In this paper, a novel fast nonsingular terminal sliding mode (FNTSM) control strategy using extreme learning machine (ELM) is proposed for permanent-magnet linear motor systems. It is shown that the developed FNTSM controller is composed of an equivalent control via ELM technique, a compensation control and a reaching control. Distinguished from the traditional ELM for pattern classification, output weights of the proposed ELM are adaptively adjusted by the adaptive law in Lyapunov sense from the global stability point of view, such that the equivalent control of the proposed controller can be flexibly estimated via ELM. Not only can the strong robustness and the faster convergence rate of the closed-loop control be guaranteed, but also the dependence of system dynamics can be further alleviated in the controller design due to the implementation of the ELM. Comparative simulation results are given to validate the robust control performance of the developed controller for both step tracking and sinusoidal tracking purposes.

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Authors and Affiliations

  1. Hefei University of Technology, Hefei, 230009, China

    Jie Zhang & Ming Yu

  2. Murdoch University, Perth, WA, 6150, Australia

    Hai Wang, Amirmehdi Yazdani & Farhad Shahnia

  3. Swinburne University of Technology, Melbourne, VIC, 3122, Australia

    Zhenwei Cao & Jinchuan Zheng

Authors
  1. Jie Zhang
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  2. Hai Wang
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  3. Zhenwei Cao
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  4. Jinchuan Zheng
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  5. Ming Yu
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  6. Amirmehdi Yazdani
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  7. Farhad Shahnia
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Correspondence to Hai Wang.

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Zhang, J., Wang, H., Cao, Z. et al. Fast nonsingular terminal sliding mode control for permanent-magnet linear motor via ELM. Neural Comput & Applic 32, 14447–14457 (2020). https://doi.org/10.1007/s00521-019-04502-4

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  • DOI: https://doi.org/10.1007/s00521-019-04502-4

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