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Actuators
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Piezoelectric Actuators and Motors: State-of-the-Art and Perspectives for Actuators
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Piezoelectric Actuators and Motors: State-of-the-Art and Perspectives for Actuators

A special issue of Actuators (ISSN 2076-0825). This special issue belongs to the section "Actuator Materials".

Deadline for manuscript submissions: 20 October 2026 | Viewed by 1784

Special Issue Editors

Prof. Dr. Hu Huang

E-Mail Website
Guest Editor
Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China
Interests: precision machines and instruments; mechanical properties of materials; surface modification of materials
Special Issues, Collections and Topics in MDPI journals
Dr. Zhixin Yang

E-Mail Website
Guest Editor
School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130012, China
Interests: piezoelectric precision drive technology; precision instruments
Dr. Zhi Xu

E-Mail Website
Guest Editor
School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130012, China
Interests: piezoelectric precision actuators

Special Issue Information

Dear Colleagues,

Piezoelectric actuators and motors working by the inverse piezoelectric effect of piezoelectric materials, could achieve precise mechanical motion through electrical excitation. Due to the crucial characteristics of micro/nanometer-scale accuracy, rapid dynamic response and immune electromagnetic interference, they have revolutionized diverse fields such as precision engineering, medical devices, aerospace systems, robotics and life sciences.

This Special Issue, titled “Piezoelectric Actuators and Motors: State-of-the-Art and Perspectives for Actuators”, aims to showcase cutting-edge research, breakthrough innovations and forward-looking insights shaping the future of piezoelectric actuation. Contributions included in this Special Issue explore advancements in novel driving principles, enhanced modeling techniques, innovative design and manufacturing strategies, self-sensing capabilities, advanced control algorithms and transformative applications.

These studies aim to pave the way for the next generation of piezoelectric actuators and motors. Original research papers as well as review papers from both academia and industry are welcome.

Prof. Dr. Hu Huang
Dr. Zhixin Yang
Dr. Zhi Xu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Actuators is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced design of piezoelectric actuators
  • smart piezoelectric materials
  • theoretical analysis of piezoelectric actuators
  • precision control technology
  • self-sensing for piezoelectric actuators
  • assessment and precision measurement
  • advanced manufacturing of piezoelectric actuators
  • emerging applications of piezoelectric actuators

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

23 pages, 5066 KB  
Article
Machine Learning-Assisted Output Optimization of Non-Resonant Motors
by Mengxin Sun, Pengfei Yu, Zhenwei Cao, Muzhi Zhu, Songfei Su and Lukai Zheng
Actuators 2026, 15(1), 48; https://doi.org/10.3390/act15010048 - 12 Jan 2026
Cited by 1 | Viewed by 424
Abstract
The precision drive industry has seen rapid growth, leading to an increased demand for actuators that are both highly accurate and responsive. Among these, non-resonant piezoelectric motors are particularly noteworthy. These motors are extensively employed in applications such as high-precision manufacturing, precision drug [...] Read more.
The precision drive industry has seen rapid growth, leading to an increased demand for actuators that are both highly accurate and responsive. Among these, non-resonant piezoelectric motors are particularly noteworthy. These motors are extensively employed in applications such as high-precision manufacturing, precision drug delivery, and cellular puncture, owing to their adaptable drive control and resistance to external disturbances. Given the specific requirements of these applications, it is crucial to quickly determine the relationship between the motor input parameters and output characteristics—a challenging endeavor. In this research, we examine a typical non-resonant piezoelectric motor using multiple sets of experimental data. A machine learning algorithm is employed to swiftly establish the correlation between electromechanical input parameters and output trajectory characteristics. Data are analyzed using a random forest model to understand the underlying influence mechanisms. Based on this analysis, predictions and recommendations are made to achieve optimal operating conditions for the motor. This study demonstrates that machine learning serves as an effective tool for predicting piezoelectric motor performance, facilitating rapid assessment of motor output capabilities. Full article
(This article belongs to the Special Issue Piezoelectric Actuators and Motors: State-of-the-Art and Perspectives for Actuators)
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18 pages, 13641 KB  
Article
Nonlinearity Characterization of Flexible Hinge Piezoelectric Stages Under Dynamic Preload via a Force-Dependent Prandtl–Ishlinskii Model with a Force-Analyzed Finite Element Method
by Xuchen Wang, Dong An, Zicheng Qin, Chuan Wang, Yuping Liu and Yixiao Yang
Actuators 2025, 14(8), 411; https://doi.org/10.3390/act14080411 - 19 Aug 2025
Cited by 2 | Viewed by 809
Abstract
The operational performance of Flexible Hinge Piezoelectric Stages (FHPSs), essential components in precision engineering, is fundamentally constrained by the inherent hysteresis of the piezoelectric actuator (PEA). A significant deficiency in prevailing characterization methods is their failure to consider the dynamic nature of the [...] Read more.
The operational performance of Flexible Hinge Piezoelectric Stages (FHPSs), essential components in precision engineering, is fundamentally constrained by the inherent hysteresis of the piezoelectric actuator (PEA). A significant deficiency in prevailing characterization methods is their failure to consider the dynamic nature of the mechanical preload exerted by the flexible hinge. This position-dependent preload induces substantial deviations in the PEA’s response characteristics, thereby compromising the predictive accuracy of conventional design frameworks. To address this limitation, this paper proposes a Force-Dependent Prandtl–Ishlinskii (FPI) model that explicitly formulates the PEA’s hysteretic behavior as a function of variable preload conditions. The FPI model is subsequently integrated into a comprehensive FPI-FFEM characterization framework. Within this framework, a Force-analyzed Finite Element Method (FFEM) is utilized to compute the dynamic preload throughout the actuator’s operational stroke. This information, notably neglected in conventional FEM analysis, is essential to the fidelity of the proposed FPI model. Experimental validation demonstrates the superior fidelity of the FPI model in comparison to the traditional PI model for tracking preload-induced nonlinearities. Furthermore, the complete FPI-FFEM framework exhibits substantially enhanced prediction accuracy relative to both conventional PI-FEM and advanced LDPI-FEM methodologies, as demonstrated by a significant reduction in the Mean Absolute Error (MAE). Full article
(This article belongs to the Special Issue Piezoelectric Actuators and Motors: State-of-the-Art and Perspectives for Actuators)
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