Hysteresis modeling of piezoelectric actuators with the frequency-dependent behavior using a hybrid model

Qian, Cheng; Ouyang, Qian; Song, Yulai; Zhao, Wei

doi:10.1177/0954406219897089

Cited by 6 publications

(4 citation statements)

References 37 publications

(36 reference statements)

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“…Wei et al (2014) employed the extended LSA manner-recursive LSA that is a variation of LSA and dynamically estimates unknown system parameters, and a limited memory approach to complete accurate online identification for asymmetrical BW model parameters. Fujii et al (2018) utilized a recursive LSA to identify a discrete classical BW model of a bimorph-type PA. Qian et al (2020) regulated the classical BW model parameters of a PA at various frequencies by least-squares support vector machine accurately.…”

Section: System Modelingmentioning

confidence: 99%

A survey of Bouc-Wen hysteretic models applied to piezo-actuated mechanical systems: Modeling, identification, and control

Cai

Dong

Nagamune

2023

Journal of Intelligent Material Systems and Structures

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Hysteretic nonlinearity behavior ubiquitously occurs in mechanical systems, particularly in high-precision instruments, which severely degrades system output performance. Consequently, it is unavoidable to establish an accurate hysteretic model to describe the hysteretic characteristic of various mechanical systems and to compensate for the system error caused by hysteresis. The piezo-actuated mechanism is one of the most frequent mechanical systems that occurs hysteretic phenomenon, explained in detail in this survey. Bouc-Wen (BW) model has been popularly applied in modeling hysteretic attributes due to the outstanding advantage of simple structure and identification process. This paper presents the latest BW model applications and investigates different BW models, identification methods, and control strategies in light of various application demands based on the BW model systematically. In addition, this survey is meaningful in choosing an appropriate modeling approach and control means for system design according to the distinct requirements, and in providing future research direction.

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Section: System Modelingmentioning

confidence: 99%

A survey of Bouc-Wen hysteretic models applied to piezo-actuated mechanical systems: Modeling, identification, and control

Cai

Dong

Nagamune

2023

Journal of Intelligent Material Systems and Structures

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“…Some studies have tried to develop different parameter identification methods. In addition to the classical least squares algorithm, 17 meta-optimization such as particle swarm algorithm (PSO), 18 genetic algorithm 19 and fish swarm algorithm (AF) 20 are applied to the parameter identification of the model. And some studies have verified that Antlion algorithm (ALO) is robust and simple.…”

Section: Introductionmentioning

confidence: 99%

Parameter identification of Duhem model based on antlion-fish swarm hybrid algorithm and robust backstepping sliding mode control for rate-dependent hysteresis of piezoelectric actuators

Zeyu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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A new parameter identification method of Duhem model based on antlion-fish swarm hybrid algorithm is proposed to characterize the rate-dependent hysteresis. The unknown piecewise functions in Duhem model is identified by a hybrid algorithm. Antlion optimization (ALO) algorithm and artificial fish (AF) swarm algorithm are switched in order of execution and their iterative data are fused to form the antlion-fish swarm hybrid algorithm. The comparison experiment shows the hybrid algorithm has the advantages of fast convergence and high precision. In order to compensate the rate-dependent hysteresis of PEA, a robust backstepping sliding mode feedback controller with feedforward inverse Duhem model compensator are designed. The comparative experimental results of displacement tracking show that this method has good tracking performance. The practicability and effectiveness of the method are verified.

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“…Nematollahi et al 15 suggested a wavelet-based neural network for inverse identification of piezoelectric beam. Qian et al 16 introduced a hybrid least-squares support vector machine and Bouc-Wen model to model the ratedependent hysteresis of piezoelectric actuators. Zhang et al 17 investigated an optimal hysteresis model of PZT actuator using particle swarm optimization-based neural network.…”

Section: Introductionmentioning

confidence: 99%

Hysteresis modelling and compensation for piezoelectric actuator using Jaya-BP neural network

Sơn

Ánh

2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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This paper proposes a new training algorithm using a hybrid Jaya-back propagation algorithm (called H-Jaya) to optimize the neural network weights, which is applied to identify the nonlinear hysteresis Piezoelectric actuator based on the experimental input-output data. The identified H-Jaya-neural model will be used to design an advanced feed-forward (FF) controller for compensating the hysteresis nonlinearity. Furthermore as to improve the tracking performance, a feed-forward-feedback control scheme is conducted. To evaluate the effectiveness of the proposed approach, firstly, it is tested through identifying the nonlinear hysteresis of Piezoelectric (PZT) actuator and compared with other meta-heuristic techniques, including differential evolution (DE), particle swarm optimization (PSO), and Jaya. Then, the accuracy of the hysteresis model-based compensator is evaluated under various control experiments using the piezoelectric actuator. The results of experiments executed on PZT actuator configured with a PZS001 from Thorlabs prove that the proposed approach obtains an excellent performance in hysteresis modeling and compensation.

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Hysteresis modeling of piezoelectric actuators with the frequency-dependent behavior using a hybrid model

Cited by 6 publications

References 37 publications

A survey of Bouc-Wen hysteretic models applied to piezo-actuated mechanical systems: Modeling, identification, and control

A survey of Bouc-Wen hysteretic models applied to piezo-actuated mechanical systems: Modeling, identification, and control

Parameter identification of Duhem model based on antlion-fish swarm hybrid algorithm and robust backstepping sliding mode control for rate-dependent hysteresis of piezoelectric actuators

Hysteresis modelling and compensation for piezoelectric actuator using Jaya-BP neural network

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