Discrete-Time Linear Quadratic Tracking Control for Piezoelectric ceramic actuators

To mitigate the effects of hysteresis nonlinearity in piezoelectric ceramic actuators and enhance the tracking accuracy of piezoelectric micro-positioning platforms, a Hammerstein model is developed to characterize the system. A hysteresis compensator is designed based on the Bouc-Wen model to improve the system’s linearity. To address incomplete hysteresis compensation and external disturbances, a discrete-time linear quadratic optimal tracking (DLQT) control strategy based on Kalman filtering is employed to enhance the tracking accuracy. A Kalman filter is used to estimate the system states. The DLQT controller comprises a feedforward term that enables the system output to track the reference signal and a feedback term that ensures closed-loop stability. The hardware-in-the-loop experiments without load and with load show that the proposed control strategy can effectively improve the tracking control accuracy and robustness of the piezoelectric micropositioning platform.

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Publication Details

Published
2025-07-18
DOI
https://doi.org/10.1109/eeais66172.2025.11170522
Primary Topic
Iterative Learning Control Systems
Type
article
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article

Discrete-Time Linear Quadratic Tracking Control for Piezoelectric ceramic actuators

Shuyou Yu, Xiaodong Zhao, Dongmei Liu, Xuan Li
Iterative Learning Control Systems
article

Discrete-Time Linear Quadratic Tracking Control for Piezoelectric ceramic actuators

Shuyou Yu, Xiaodong Zhao, Dongmei Liu, Xuan Li
article en

Abstract

To mitigate the effects of hysteresis nonlinearity in piezoelectric ceramic actuators and enhance the tracking accuracy of piezoelectric micro-positioning platforms, a Hammerstein model is developed to characterize the system. A hysteresis compensator is designed based on the Bouc-Wen model to improve the system’s linearity. To address incomplete hysteresis compensation and external disturbances, a discrete-time linear quadratic optimal tracking (DLQT) control strategy based on Kalman filtering is employed to enhance the tracking accuracy. A Kalman filter is used to estimate the system states. The DLQT controller comprises a feedforward term that enables the system output to track the reference signal and a feedback term that ensures closed-loop stability. The hardware-in-the-loop experiments without load and with load show that the proposed control strategy can effectively improve the tracking control accuracy and robustness of the piezoelectric micropositioning platform.

Jilin University (CN), Changchun University (CN)
Openalex Percentile: Top 67%
Iterative Learning Control Systems
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Discrete-Time Linear Quadratic Tracking Control for Piezoelectric ceramic actuators — Shuyou Yu, Xiaodong Zhao, et al. · (2025) | TGRS Research Map | TGRS