IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i3p1198-d1043540.html
   My bibliography  Save this article

Experimental Analysis of Hysteresis in the Motion of a Two-Input Piezoelectric Bimorph Actuator

Author

Listed:
  • Dariusz Grzybek

    (Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland)

Abstract

This article presents a comparison of hysteresis courses in the motion of a two-input actuator (bimorph) and hysteresis in the motion of a single-input actuator (unimorph). The comparison was based on the results of laboratory and numerical experiments, the subject of which was an actuator built of three layers: a carrier layer from a glass-reinforced epoxy laminate and two piezoelectric layers from Macro Fiber Composite. The layers were glued together, and electrodes in the Macro Fiber Composite layers were connected to a system that included an analogue/digital board and a voltage amplifier. The main purpose of this research was to compare the characteristic points of the hysteresis curves of the displacement of the bimorph actuator with the characteristic points of the hysteresis curves of the unimorph actuator. Based on the research results, it was noticed that, in the bimorph, the maximum hysteresis and mean hysteresis values increase faster than the maximum displacement of a beam tip. However, values of characteristic input voltages for hysteresis loops—voltage corresponding to a maximum displacement of the actuator beam tip and voltage corresponding to maximum hysteresis—are almost the same for the bimorph and unimorph. From a practical point of view, it was noticed that the unimorph is a better choice compared to the bimorph in applications in which high changes in frequencies of input voltages appear.

Suggested Citation

  • Dariusz Grzybek, 2023. "Experimental Analysis of Hysteresis in the Motion of a Two-Input Piezoelectric Bimorph Actuator," Energies, MDPI, vol. 16(3), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1198-:d:1043540
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/3/1198/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/3/1198/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paolo Tamburrano & Francesco Sciatti & Andrew R. Plummer & Elia Distaso & Pietro De Palma & Riccardo Amirante, 2021. "A Review of Novel Architectures of Servovalves Driven by Piezoelectric Actuators," Energies, MDPI, vol. 14(16), pages 1-23, August.
    2. Dariusz Grzybek, 2022. "Control System for Multi-Input and Simple-Output Piezoelectric Beam Actuator Based on Macro Fiber Composite," Energies, MDPI, vol. 15(6), pages 1-20, March.
    3. Ander Chouza & Oscar Barambones & Isidro Calvo & Javier Velasco, 2019. "Sliding Mode-Based Robust Control for Piezoelectric Actuators with Inverse Dynamics Estimation," Energies, MDPI, vol. 12(5), pages 1-19, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiaohuan Lai & Haipeng Pan & Xinlong Zhao, 2019. "Adaptive Control for Pure-Feedback Nonlinear Systems Preceded by Asymmetric Hysteresis," Energies, MDPI, vol. 12(24), pages 1-13, December.
    2. Mohamed Derbeli & Cristian Napole & Oscar Barambones & Jesus Sanchez & Isidro Calvo & Pablo Fernández-Bustamante, 2021. "Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications," Energies, MDPI, vol. 14(22), pages 1-31, November.
    3. Cristian Napole & Oscar Barambones & Isidro Calvo & Javier Velasco, 2020. "Feedforward Compensation Analysis of Piezoelectric Actuators Using Artificial Neural Networks with Conventional PID Controller and Single-Neuron PID Based on Hebb Learning Rules," Energies, MDPI, vol. 13(15), pages 1-16, August.
    4. Cristian Napole & Oscar Barambones & Mohamed Derbeli & Isidro Calvo & Mohammed Yousri Silaa & Javier Velasco, 2021. "High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks," Mathematics, MDPI, vol. 9(3), pages 1-20, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1198-:d:1043540. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.