Hysteresis-Estimator-Based Adaptive Fuzzy Control for Piezoelectric Micro-Positioning Stage With Time-Varying Output Constraints

This brief addresses the high-precision motion control of piezoelectric micro-positioning stages (PMPSs) subject to time-varying output constraints, input hysteresis nonlinearity, and system uncertainties. The key features of the developed hysteresis-estimator-based adaptive fuzzy control (HEAFC) me...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on circuits and systems. II, Express briefs Vol. 72; no. 10; pp. 1418 - 1422
Main Authors Nie, Linlin, Yu, Yewei, Zhou, Miaolei, Zhang, Xiuyu, Su, Chun-Yi
Format Journal Article
LanguageEnglish
Published New York IEEE 01.10.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptation models
Adaptive control
adaptive fuzzy control
Closed loops
Constraints
Control theory
Estimation
Fuzzy control
Fuzzy logic
Fuzzy systems
Human-robot interaction
Hysteresis
hysteresis nonlinearity
Micropositioning
Motion control
output constraints
Piezoelectric micro-positioning stage
Piezoelectricity
Real time
Real-time systems
Transforms
Transient analysis
Vectors
Online AccessGet full text
ISSN1549-7747
1558-3791
DOI10.1109/TCSII.2025.3601156

Cover

More Information
Summary:This brief addresses the high-precision motion control of piezoelectric micro-positioning stages (PMPSs) subject to time-varying output constraints, input hysteresis nonlinearity, and system uncertainties. The key features of the developed hysteresis-estimator-based adaptive fuzzy control (HEAFC) method are as follows. First, an asymmetric rate-dependent hysteresis operator is used to construct an extended fuzzy input space, enabling a fuzzy dynamic hysteresis estimator (FDHE) for real-time hysteresis estimation via adaptive fuzzy logic. Second, auxiliary functions are embedded into a backstepping-like control framework to explicitly handle time-varying output constraints. Moreover, by leveraging the structural characteristics of fuzzy systems, the HEAFC scheme avoids repeated differentiation or filtering of virtual control laws. This feature can substantially simplify the control structure. The HEAFC method guarantees prespecified constraint satisfaction and high-accuracy trajectory tracking. Lyapunov-based analysis ensures closed-loop stability, and experimental results on a PMPS demonstrate the effectiveness of the HEAFC strategy.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1549-7747
1558-3791
DOI:10.1109/TCSII.2025.3601156