Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis

Xiuyu Zhang; Hongzhi Xu; Zhi Li; Feng Shu; Xinkai Chen

doi:10.1109/TSMC.2022.3231261

Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis

Xiuyu Zhang, Hongzhi Xu, Zhi Li, Feng Shu, Xinkai Chen

Research output: Contribution to journal › Article › peer-review

Abstract

In this article, an adaptive neural piecewise implicit inverse control strategy is proposed to effectively compensate for butterfly hysteresis effectively. First, a new butterfly Krasnoselskii–Pokrovskii (BKP) model is developed for the double-loop butterfly hysteresis characteristics. Second, an adaptive neural piecewise implicit inverse control strategy is designed to mitigate the butterfly-like hysteresis without constructing its analytical inverse model. Finally, experimental results on the dielectric elastomer actuator (DEA) motion control platform demonstrate the effectiveness of the adaptive neural piecewise implicit inverse control strategy.

Original language	English
Pages (from-to)	1-12
Number of pages	12
Journal	IEEE Transactions on Systems, Man, and Cybernetics: Systems
DOIs	https://doi.org/10.1109/TSMC.2022.3231261
Publication status	Accepted/In press - 2023

Keywords

Adaptation models
Adaptive neural control
dielectric elastomer actuators (DEAs)
Hysteresis
hysteresis nonlinearity
implicit inverse compensation
Kernel
Mathematical models
Motion control
Piezoelectric actuators
Process control

ASJC Scopus subject areas

Software
Control and Systems Engineering
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TSMC.2022.3231261

Cite this

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title = "Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis",

abstract = "In this article, an adaptive neural piecewise implicit inverse control strategy is proposed to effectively compensate for butterfly hysteresis effectively. First, a new butterfly Krasnoselskii–Pokrovskii (BKP) model is developed for the double-loop butterfly hysteresis characteristics. Second, an adaptive neural piecewise implicit inverse control strategy is designed to mitigate the butterfly-like hysteresis without constructing its analytical inverse model. Finally, experimental results on the dielectric elastomer actuator (DEA) motion control platform demonstrate the effectiveness of the adaptive neural piecewise implicit inverse control strategy.",

keywords = "Adaptation models, Adaptive neural control, dielectric elastomer actuators (DEAs), Hysteresis, hysteresis nonlinearity, implicit inverse compensation, Kernel, Mathematical models, Motion control, Piezoelectric actuators, Process control",

author = "Xiuyu Zhang and Hongzhi Xu and Zhi Li and Feng Shu and Xinkai Chen",

note = "Publisher Copyright: IEEE",

year = "2023",

doi = "10.1109/TSMC.2022.3231261",

language = "English",

pages = "1--12",

journal = "IEEE Transactions on Systems, Man, and Cybernetics: Systems",

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T1 - Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis

AU - Zhang, Xiuyu

AU - Xu, Hongzhi

AU - Li, Zhi

AU - Shu, Feng

AU - Chen, Xinkai

N1 - Publisher Copyright: IEEE

PY - 2023

Y1 - 2023

N2 - In this article, an adaptive neural piecewise implicit inverse control strategy is proposed to effectively compensate for butterfly hysteresis effectively. First, a new butterfly Krasnoselskii–Pokrovskii (BKP) model is developed for the double-loop butterfly hysteresis characteristics. Second, an adaptive neural piecewise implicit inverse control strategy is designed to mitigate the butterfly-like hysteresis without constructing its analytical inverse model. Finally, experimental results on the dielectric elastomer actuator (DEA) motion control platform demonstrate the effectiveness of the adaptive neural piecewise implicit inverse control strategy.

AB - In this article, an adaptive neural piecewise implicit inverse control strategy is proposed to effectively compensate for butterfly hysteresis effectively. First, a new butterfly Krasnoselskii–Pokrovskii (BKP) model is developed for the double-loop butterfly hysteresis characteristics. Second, an adaptive neural piecewise implicit inverse control strategy is designed to mitigate the butterfly-like hysteresis without constructing its analytical inverse model. Finally, experimental results on the dielectric elastomer actuator (DEA) motion control platform demonstrate the effectiveness of the adaptive neural piecewise implicit inverse control strategy.

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KW - Adaptive neural control

KW - dielectric elastomer actuators (DEAs)

KW - Hysteresis

KW - hysteresis nonlinearity

KW - implicit inverse compensation

KW - Kernel

KW - Mathematical models

KW - Motion control

KW - Piezoelectric actuators

KW - Process control

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Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis

Abstract

Keywords

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