Search Results (40)

This paper presents a modeling framework for hysteretically nonlinear piezoelectric composite beams using functional differential equations (FDEs). While linear piezoelectric models are well established, they fail to capture the complex nonlinear behaviors that emerge at higher electric field strengths, particularly history-dependent hysteresis effects. This paper develops a cascade model that integrates a high-dimensional linear piezoelectric composite beam representation with a nonlinear Krasnosel’skii–Pokrovskii (KP) hysteresis operator. The resulting system is formulated using a state-space model where the input voltage undergoes a history-dependent transformation. Through modal expansion and discretization of the Preisach plane, we derive a tractable numerical implementation that preserves essential nonlinear phenomena. Numerical investigations demonstrate how system parameters, including the input voltage amplitude, and hysteresis parameters significantly influence the dynamic response, particularly the shape and amplitude of limit cycles. The results reveal that while the model accurately captures memory-dependent nonlinearities, it depends on numerous real and distributed parameters, highlighting the need for efficient reduced-order modeling approaches. This work provides a foundation for understanding and predicting the complex behavior of piezoelectric systems with hysteresis, with potential applications in vibration control, energy harvesting, and precision actuation. Full article

Hysteresis is a nonlinear phenomenon found in many physical systems, including soft viscoelastic actuators, where it poses significant challenges to their application and performance. Consequently, developing accurate hysteresis models is essential for the effective design and optimization of soft actuators. Moreover, a reliable model can be used to design compensators that mitigate the negative effects of hysteresis, improving closed-loop control accuracy and expanding the applicability of soft actuators in robotics. Physics-based approaches for modeling hysteresis in soft actuators offer valuable insights into the underlying material behavior. Nevertheless, they are often highly complex, making them impractical for real-world applications. Instead, phenomenological models provide a more feasible solution by representing hysteresis through input–output mappings based on experimental data. To effectively fit these phenomenological models, it is essential to rely on sensing data collected from real actuators. In this context, the primary objective of this work is a comprehensive comparative evaluation of the efficiency and performance of representative phenomenological hysteresis models (e.g., Bouc–Wen and Prandtl-Ishlinskii) using experimental data obtained from a pneumatic bending actuator made of a viscoelastic material. This evaluation suggests that the Generalized Prandtl–Ishlinskii model achieves the highest modeling accuracy, while the Preisach model with a probabilistic density function formulation excels in terms of parameter compactness. Full article

The present work aspires to contribute to the discussion on the relationship between macroscopic measurements and microstructure, helping establish a methodology that will allow the quantitative assessment of the effect of strain on magnetic properties in the plastic deformation regime. In particular, we study the effect of strain on the magnetization process as a result of varying the anisotropy profile at the grain level. Results on micromagnetic calculations of hysteresis loops for various configurations of magnetic anisotropy are shown and discussed against the interplay between the energy terms involved in the calculations, namely anisotropy, demagnetizing, and exchange. The results are in line with previously obtained results using vector Preisach modeling with the Stoner–Wohlfarth model acting both as a switching and rotation mechanism. The hysteresis loop phenomenology is consistent with the emergence of a hard phase in the form of a boundary around soft grains which is assumed to be the result of the onset of compressive stresses in the plastic region. Future research will be oriented toward the study of the effect of the secondary peak in differential permeability, which is observed experimentally in the plastic deformation region, and its dependence on the angle of misalignment between the hard boundary and the soft grain. Full article

The development of innovative materials, based on the modern technologies and processes, is the key factor to improve the energetic sustainability and reduce the environmental impact of electrical equipment. In particular, the modeling of magnetic hysteresis is crucial for the design and construction of electrical and electronic devices. In recent years, additive manufacturing techniques are playing a decisive role in the project and production of magnetic elements and circuits for applications in various engineering fields. To this aim, the use of the deep learning paradigm, integrated with the most common models of the magnetic hysteresis process, has become increasingly present in recent years. The intent of this paper is to provide the features of a wide range of deep learning tools to be applied to magnetic hysteresis context and beyond. The possibilities of building neural networks in hybrid form are innumerable, so it is not plausible to illustrate them in a single paper, but in the present context, several neural networks used in the scientific literature, integrated with various hysteretic mathematical models, including the well-known Preisach model, are compared. It is shown that this hybrid approach not only improves the modeling of hysteresis by significantly reducing computational time and efforts, but also offers new perspectives for the analysis and prediction of the behavior of magnetic materials, with significant implications for the production of advanced devices. Full article

This article delivers a new Preisach model representing the correlation between the elastoplastic behavior of structural mild steel under axial monotonic and cyclic loading with damage. The newly formed model is based on the experimentally defined correlation between axial monotonic and cyclic behavior of structural mild steel. To examine the monotonic and cyclic behavior of structural mild steel and find fitting material properties for the model, monotonic and cyclic axial tensile tests are performed. Tests are executed on coupons of the commonly used European structural steel S275. The model represents a mathematical description of modified single-crystal material behavior under monotonic loading. Two different approaches were used to describe damage in the multilinear mechanical model. The excellent agreement with experimental results is achieved by infinitely linking many single-crystal elements in parallel, forming the polycrystalline model. This model provides a good solution for everyday engineering practice due to its geometric representation in the form of the Preisach triangle and the lower costs of monotonic tests used to define material properties compared to cyclic tests. Full article

Shape Memory Alloys (SMAs) are used to design actuators, which are one of the most fascinating applications of SMA. Usually, they are on-off actuators because, in the case of continuous actuators, the nonlinearity of their characteristics is the problem. The main problem, especially in control systems in these actuators, is a hysteretic loop. There are many models of hysteresis, but from a control theory point of view, they are not helpful. This study used an artificial neural network (ANN) to model the SMA actuator hysteresis. The ANN structure and training method are presented in the paper. Data were generated from the Preisach model for training. This approach allowed for quick and controllable data generation, making experiments thoroughly planned and repeatable. The advantage and disadvantage of this approach is the lack of disturbances. The paper’s main goal is to model an SMA actuator. Additionally, it explores whether and how an ANN can describe and model the hysteresis loop. A literature review shows that ANNs are used to model hysteresis, but to a limited extent; this means that the hysteresis loop was modelled with a hysteretic element. Full article

In this paper, the Preisach model for magnetic hysteresis of grain-oriented silicon steel under PWM excitation is improved. First, an improved Preisach model for the magnetic hysteresis of grain-oriented silicon steel under PWM excitation is proposed. Second, the experimental platform for grain-oriented silicon steel sheets under PWM excitation is established. Finally, by comparative analysis, it is concluded that the error of the improved model is far less than that of the classical model (the error here refers to the discrepancy between experimental results and theoretical model predictions). The improved model is 1.4% to 9% more accurate than the classical model. A more accurate model can provide more accurate material parameters for the calculation of the magnetic field in the transformer core, which is of great significance to the production and design of the transformer. Full article

Piezoelectric ceramic actuators have the advantages of fast response speed and high positioning accuracy and are widely used in micro-machinery, aerospace, precision machining machinery, and other precision positioning fields. However, hysteretic nonlinearity has a great influence on the positioning accuracy of piezoelectric ceramic actuators, so it is necessary to establish a hysteretic model to solve this problem. In this paper, the principles of the Preisach model, the Prandtl Ishilinskii (PI) model, the Maxwell model, the Duhem model, the Bouc–Wen model, and the Hammerstein model and their application and development in piezoelectric hysteresis modeling are described in detail. At the same time, the classical model, the asymmetric model and the rate-dependent model of these models are described in detail, and the application of the inverse model corresponding to these models in the feedforward compensation is explained in detail. At the end of the paper, the methods of inverse model acquisition and control frequency of these models are compared. In addition, the future research trend of the hysteresis model is also prospected. The ideas and suggestions highlighted in this paper will guide the development of piezoelectric hysteresis models. Full article

Three-dimensional printing is a promising technology that offers increased freedom to create topologically optimised electrical machine designs with a much smaller layer thickness achievable with the current, laminated steel-sheet-based technology. These composite materials have promising magnetic behaviour, which can be competitive with the current magnetic materials. Accurately calculating the iron losses is challenging due to magnetic steels’ highly nonlinear hysteretic behaviour. Many numerical methodologies have been developed and applied in FEM-based simulations from the first introduced Steinmetz formulae. However, these old curve-fitting-based iron loss models are still actively used in modern finite-element solvers due to their simplicity and high computational demand for more-accurate mathematical methods, such as Preisach- or Jiles–Atherton-model-based calculations. In the case of 3D-printed electrical machines, where the printed material can have a strongly anisotropic behaviour and it is hard to define a standardised measurement, the applicability of the curve-fitting-based iron loss methodologies is limited. The following paper proposes an overview of the current problems and solutions for iron loss calculation and measurement methodologies and discusses their applicability in designing and optimising 3D-printed electrical machines. Full article

To describe the hysteresis nonlinearities in smart actuators, numerous models have been presented in the literature, among which the Preisach operator is the most effective due to its capability to capture multi-loop or sophisticated hysteresis curves. When such an operator is coupled with uncertain nonlinear dynamics, especially in noncanonical form, it is a challenging problem to develop techniques to cancel out the hysteresis effects and, at the same time, achieve asymptotic tracking performance. To address this problem, in this paper, we investigate the problem of iterative inverse-based adaptive control for uncertain noncanonical nonlinear systems with unknown input Preisach hysteresis, and a new adaptive version of the closest-match algorithm is proposed to compensate for the Preisach hysteresis. With our scheme, the stability and convergence of the closed-loop system can be established. The effectiveness of the proposed control scheme is illustrated through simulation and experimental results. Full article

Transformers, reactors and other electrical equipment often work under harmonics and DC-bias working conditions. It is necessary to quickly and accurately simulate the hysteresis characteristics of soft magnetic materials under various excitation conditions in order to achieve accurate calculations of core loss and the optimal design of electrical equipment. Based on Preisach hysteresis model, a parameter identification method for asymmetric hysteresis loop simulation is designed and applied to the simulation of hysteresis characteristics under bias conditions of oriented silicon steel sheets. In this paper, the limiting hysteresis loops of oriented silicon steel sheets are obtained through experiments under different working conditions. The first-order reversal curves(FORCs) with asymmetric characteristics is generated numerically, and then the Everett function is established under different DC bias conditions. The hysteresis characteristics of the oriented silicon steel sheets under harmonics and DC bias are simulated by improving FORCs identification method of the Preisach model. By comparing the results of simulation and experiment, the effectiveness of the proposed method is verified, so as to provide an important reference for material production and application. Full article

The nonlinear hysteresis phenomenon can occur in piezoelectric-driven nanopositioning systems and can lead to reduced positioning accuracy or result in a serious deterioration of motion control. The Preisach method is widely used for hysteresis modeling; however, for the modeling of rate-dependent hysteresis, where the output displacement of the piezoelectric actuator depends on the amplitude and frequency of the input reference signal, the desired accuracy cannot be achieved with the classical Preisach method. In this paper, the Preisach model is improved using least-squares support vector machines (LSSVMs) to deal with the rate-dependent properties. The control part is then designed and consists of an inverse Preisach model to compensate for the hysteresis nonlinearity and a two-degree-of-freedom (2-DOF) H-infinity feedback controller to enhance the overall tracking performance with robustness. The main idea of the proposed 2-DOF H-infinity feedback controller is to find two optimal controllers that properly shape the closed-loop sensitivity functions by imposing some templates in terms of weighting functions in order to achieve the desired tracking performance with robustness. The achieved results with the suggested control strategy show that both hysteresis modeling accuracy and tracking performance are significantly improved with average root-mean-square error (RMSE) values of 0.0107 μm and 0.0212 μm, respectively. In addition, the suggested methodology can achieve better performance than comparative methods in terms of generalization and precision. Full article

There are several models for magnetic hysteresis. Their key purposes are to model magnetization curves with a history dependence to achieve hysteresis cycles without a frequency dependence. There are different approaches to handling history dependence. The two main categories are Duhem-type models and Preisach-type models. Duhem models handle it via a simple directional dependence on the flux rate, without a proper memory. While the Preisach type model handles it via memory of the point where the direction of the flux rate is changed. The most common Duhem model is the phenomenological Jiles–Atherton model, with examples of other models including the Coleman–Hodgdon model and the Tellinen model. Examples of Preisach type models are the classical Preisach model and the Prandtl–Ishlinskii model, although there are also many other models with adoptions of a similar history dependence. Hysteresis is by definition rate-independent, and thereby not dependent on the speed of the alternating flux density. An additional rate dependence is still important and often included in many dynamic hysteresis models. The Chua model is common for modeling non-linear dynamic magnetization curves; however, it does not define classical hysteresis. Other similar adoptions also exist that combine hysteresis modeling with eddy current modeling, similar to how frequency dependence is included in core loss modeling. Most models are made for scalar values of alternating fields, but there are also several models with vector generalizations that also consider three-dimensional directions. Full article

Magnetorheological elastomers (MREs) are a type of smart material that can change their mechanical properties in response to external magnetic fields. These unique properties make them ideal for various applications, including vibration control, noise reduction, and shock absorption. This paper presents an approach for modeling the impact behavior of MREs. The proposed model uses a combination of exponential functions arranged in a multi-layer Preisach model to capture the nonlinear behavior of MREs under impact loads. The model is trained using particle swarm optimization (PSO) and validated using experimental data from drop impact tests conducted on MRE samples under various magnetic field strengths. The results demonstrate that the proposed model can accurately predict the impact behavior of MREs, making it a useful tool for designing MRE-based devices that require precise control of their impact response. The model’s response closely matches the experimental data with a maximum prediction error of 10% or less. Furthermore, the interpolated model’s response is in agreement with the experimental data with a maximum percentage error of less than 8.5%. Full article

The incorporation of hysteresis models in computational electromagnetic software is of paramount importance for the accurate prediction of the ferromagnetic devices’ performance. The Preisach and Jiles-Atherton (J-A) models are frequently used for this purpose. The former is more accurate and can represent a broad range of magnetic materials, but it is computationally expensive. The latter is more efficient but can accurately model only soft ferromagnetic materials. In this paper, a recently proposed hysteresis model, referred to as the D’Aloia-Di Francesco-De Santis (D-D-D) model, is shown to have the best trade-off between accuracy and computational burden. For the first time, a numerical comparison between the Preisach, J-A and D-D-D models is provided for a large class of hysteresis loops including soft, semi-hard and hard ferromagnetic materials. Full article