Identification of Preisach Model Parameters Based on an Improved Particle Swarm Optimization Method for Piezoelectric Actuators in Micro-Manufacturing Stages

Lei, Yang; Ding, Bingxiao; Liao, Wenhu; Li, Yangmin

doi:10.3390/mi13050698

Cited by 23 publications

(13 citation statements)

References 23 publications

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“…A related scientific and technical problem is the identification of the parameters of different hysteresis models [190][191][192][193]. Various methods for calculating the characteristics of the Preisach converter are used in [194][195][196][197][198][199]. For example, work [200] suggests the choice of the density measure expressed as…”

Section: Technical Systemsmentioning

confidence: 99%

The Preisach model of hysteresis: fundamentals and applications

Semenov,

Borzunov,

Meleshenko

et al. 2024

Phys. Scr.

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The Preisach model is a well-known model of hysteresis in the modern nonlinear science. This paper provides an overview of works that are focusing on the study of dynamical systems from various areas (physics, economics, biology), where the Preisach model plays a key role in the formalization of hysteresis dependencies. Here we describe the input-output relations of the classical Preisach operator, its basic properties, methods of constructing the output using the demagnetization function formalism, a generalization of the classical Preisach operator for the case of vector input-output relations. Various generalizations of the model are described here in relation to systems containing ferromagnetic and ferroelectric materials. The main attention we pay to experimental works, where the Preisach model has been used for analytic description of the experimentally observed results. Also, we describe a wide range of the technical applications of the Preisach model in such fields as energy storage devices, systems under piezoelectric effect, models of systems with long-term memory. The properties of the Preisach operator in terms of reaction to stochastic external impacts are described and a generalization of the model for the case of the stochastic threshold numbers of its elementary components is given.

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Section: Technical Systemsmentioning

confidence: 99%

The Preisach model of hysteresis: fundamentals and applications

Semenov,

Borzunov,

Meleshenko

et al. 2024

Phys. Scr.

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show abstract

“…At the same time, [84] derived an enhanced PSO and a gravitational search algorithm that have been combined for multiple MR navigation to develop an optimal path in a cluttered environment. Yang et al [85], on the other hand, improve the PSO approach by taking into consideration the identifcation of the parameter for the Preisach model as the hanging issue for decades. Li and Chou [86] developed a self-adaptive system PSO technique (SLPSO) for solving the MR a minimization multiobjective optimization problem and path planning issue.…”

Section: Neural Networkmentioning

confidence: 99%

A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots

Rafai

Adzhar

Jaini

2022

Journal of Robotics

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Mobile robots have been widely used in various sectors in the last decade. A mobile robot could autonomously navigate in any environment, both static and dynamic. As a result, researchers in the robotics field have offered a variety of techniques. This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). Classical approaches have limitations of trapping in local minima, failure to handle uncertainty, and many more. On the other hand, it is observed that heuristic approaches can solve most real-world problems and perform well after some modification and hybridization with classical techniques. As a result, many methods have been established worldwide for the path planning strategy for mobile robots. The most often utilized approaches, on the other hand, are offered below for further study.

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“…In addition to the drawbacks mentioned for the models using the Preisach/Prandtl operator, this approach is unable to model minor hysteresis loops. More recently, hysteresis modeling has been applied to shape memory alloys (Ballew and Seelecke, 2019; Han et al, 2022; Wang and Wang, 2021; Yi et al, 2021), electroactive polymers (Jiang et al, 2021), and piezoelectric actuators (Robert et al, 2001; Xie et al, 2023; Yang et al, 2022). As in the previously mentioned research on magnetostriction, these papers consider a single-input, single-output model for the respective smart materials.…”

Section: Introductionmentioning

confidence: 99%

Parameter identification for a model for multi-functional materials with hysteresis and thermodynamic compatibility

Hossain

Iyer

Clemente

et al. 2023

Journal of Intelligent Material Systems and Structures

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Multifunctional materials have tremendous potential for engineering applications as they are able to convert mechanical to electromagnetic energy and vice-versa. One of the features of this class of materials is that they show significant hysteresis, which needs to be modeled correctly in order to maximize their application potential. A method of modeling multifunctional materials that exhibit the phenomenon of hysteresis and is compatible with the laws of thermodynamics was developed recently. The model is based on the Preisach hysteresis operator and its storage function and may be interpreted as a two-input, two-output neural net with elementary hysteresis operators as the neurons. The difficulty is that the parameters in the model appear in a non-linear fashion, and there are several constraints that must be satisfied by the parameters for thermodynamic compatibility. In this article, we present a novel methodology that uses the rate-independent memory evolution properties of the Preisach operator to split the parameter estimation problem into three numerically well-conditioned, linear least squares problems with constraints. The alternative direction method of multipliers (ADMM) algorithm and accelerated proximal gradient method are used to compute the Preisach weights. Numerical results are presented over data collected from experiments on a Galfenol sample. We show that the model is able to fit not only experimental data for strain and magnetization over a wide range of magnetic fields and stress but also able to predict the response for stress and magnetic fields not used in the parameter estimation.

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Identification of Preisach Model Parameters Based on an Improved Particle Swarm Optimization Method for Piezoelectric Actuators in Micro-Manufacturing Stages

Cited by 23 publications

References 23 publications

The Preisach model of hysteresis: fundamentals and applications

The Preisach model of hysteresis: fundamentals and applications

A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots

Parameter identification for a model for multi-functional materials with hysteresis and thermodynamic compatibility

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