Piezoelectrics & Acoustooptics, Volume. 45, Issue 2, 231(2023)

Displacement Hysteresis Modeling of Piezoelectric Actuator Based on LSTM Neural Network

SHI Mengxiang1, HU Hong1, WU Hao2, and XU Xixiao2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less
    References(4)

    [1] [1] MOHITH S,UPADHYA A R,NAVIN K P,et al.Recent trends in piezoelectric actuators for precision motion and their applications:A review[J].Smart Materials and Structures,2020,30(1):013002.

    [3] [3] HUANG H,LI J,ZHAO H,et al.On the correlation between the structure and one stepping characteristic of a piezo-driven rotary actuator[J].Microsystem Technologies,2016,22(12):2821-2827.

    [7] [7] HOCHREITER S,SCHMIDHUBER J.Long short-term memory[J].Neural Computation,1997,9(8):1735-1780.

    [8] [8] WU D,ZHANG Y,OURAK M,et al.Hysteresis modeling of robotic catheters based on long short-term memory network for improved environment reconstruction[J].IEEE Robotics and Automation Letters,2021,6(2):2106-2113.

    Tools

    Get Citation

    Copy Citation Text

    SHI Mengxiang, HU Hong, WU Hao, XU Xixiao. Displacement Hysteresis Modeling of Piezoelectric Actuator Based on LSTM Neural Network[J]. Piezoelectrics & Acoustooptics, 2023, 45(2): 231

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Received: Oct. 25, 2022

    Accepted: --

    Published Online: Nov. 29, 2023

    The Author Email:

    DOI:10.11977/j.issn.1004-2474.2023.02.013

    Topics