Time-Frequency Analysis-Based Real-Time Iterative Compensation for Piezoelectric Nanopositioning Stage

Benefiting from its rapid response, high control bandwidth, and high precision, the piezoelectric actuator (PEA) has been extensively applied to various micro-nano motion circumstances. However, the inherent nonlinearities, especially the stubborn hysteresis effect, severely degrade its control and...

Full description

Saved in:
Bibliographic Details
Published in:IEEE/ASME transactions on mechatronics 2024-12, Vol.29 (6), p.4468-4479
Main Authors: Wang, Ze, Hou, Bingyang, Hu, Chuxiong, Yu, Zhu
Format: Article
Language:English
Subjects:
Accuracy
Adaptive control
Compensation
Control methods
Hysteresis
Hysteresis models
Hysteresis-model-free control
piezoelectric actuator (PEA)
Piezoelectric actuators
Real time
real-time iterative compensation (RIC)
Real-time systems
Solids
Time-frequency analysis
Tracking errors
tracking precision
Trajectory
Transforms
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Benefiting from its rapid response, high control bandwidth, and high precision, the piezoelectric actuator (PEA) has been extensively applied to various micro-nano motion circumstances. However, the inherent nonlinearities, especially the stubborn hysteresis effect, severely degrade its control and positioning accuracy. Typical PEA control methods establish the inverse-hysteresis model to compensate, so the performance is highly restricted by the modeling accuracy and sophistication. To circumvent these defects and realize precise tracking, this article has proposed a time-frequency analysis based real-time iterative compensation (TFA-RIC) method. Compared with the existing control structures, the proposed TFA-RIC has the following preponderances: first, hysteresis-model-free, second, solid tracking accuracy, and third, robust external disturbance rejection property. Meanwhile, the stability and convergence of TFA-RIC have been theoretically proven. Various comparative experiments have been conducted to verify the effectiveness and generalization of assorted control scenarios. The experimental consequences have demonstrated the apparent advantages over the benchmark iterative learning control (ILC) method. Especially when the reference trajectory is nonsmooth or the external disturbance is injected, the tracking errors of the proposed method are reduced by about 50% compared with that of ILC.
ISSN:1083-4435
1941-014X
DOI:10.1109/TMECH.2024.3375459