A survey on hysteresis modeling, identification and control
The various mathematical models for hysteresis such as Preisach, Krasnosel'skii–Pokrovskii
(KP), Prandtl–Ishlinskii (PI), Maxwell-Slip, Bouc–Wen and Duhem are surveyed in terms of …
(KP), Prandtl–Ishlinskii (PI), Maxwell-Slip, Bouc–Wen and Duhem are surveyed in terms of …
A review on computational intelligence for identification of nonlinear dynamical systems
This work aims to provide a broad overview of computational techniques belonging to the
area of artificial intelligence tailored for identification of nonlinear dynamical systems. Both …
area of artificial intelligence tailored for identification of nonlinear dynamical systems. Both …
How magnet: Machine learning framework for modeling power magnetic material characteristics
This article applies machine learning to power magnetics modeling. We first introduce an
open-source database—MagNet—which hosts a large amount of experimentally measured …
open-source database—MagNet—which hosts a large amount of experimentally measured …
MagNet-AI: Neural network as datasheet for magnetics modeling and material recommendation
This article presents the MagNet-AI platform as an online platform to demonstrate the “neural
network as datasheet” concept for–loop modeling and material recommendation of power …
network as datasheet” concept for–loop modeling and material recommendation of power …
An effective neural network approach to reproduce magnetic hysteresis in electrical steel under arbitrary excitation waveforms
A computationally efficient and robust neural network-based model to reproduce the
hysteresis phenomenon for soft ferromagnetic alloys is here presented, as well as a …
hysteresis phenomenon for soft ferromagnetic alloys is here presented, as well as a …
Modeling hysteretic nonlinear behavior of bridge aerodynamics via cellular automata nested neural network
A new approach to model aerodynamic nonlinearities in the time domain utilizing an artificial
neural network (ANN) framework with embedded cellular automata (CA) scheme has been …
neural network (ANN) framework with embedded cellular automata (CA) scheme has been …
Takagi–Sugeno fuzzy neural network hysteresis modeling for magnetic shape memory alloy actuator based on modified bacteria foraging algorithm
C Zhang, Y Yu, Y Wang, M Zhou - International Journal of Fuzzy Systems, 2020 - Springer
The magnetic shape memory alloy (MSMA)-based actuator, as a new type of actuator, has a
great application prospect in the micro-precision positioning field. However, the input-to …
great application prospect in the micro-precision positioning field. However, the input-to …
Fast design optimization method utilizing a combination of artificial neural networks and genetic algorithms for dynamic inductive power transfer systems
Multiple parameters with large nonlinear characteristics must be considered simultaneously
to design the coil dimensions of static inductive power transfer (SIPT) systems. The design of …
to design the coil dimensions of static inductive power transfer (SIPT) systems. The design of …
Advances in magnetic hysteresis modeling
E Cardelli - Handbook of Magnetic Materials, 2015 - Elsevier
The basic physical processes can be rigorously treated using the quantum mechanics. This
is done at atomic level and is far from the aim of this chapter. Other approaches at …
is done at atomic level and is far from the aim of this chapter. Other approaches at …
A neural networks model for hysteresis nonlinearity
L Chuntao, T Yonghong - Sensors and Actuators A: Physical, 2004 - Elsevier
This paper presents a new approach for modeling hysteresis nonlinearity in piezo-actuators.
Under a mild assumption, a mapping, which can be approximated by multi-layer neural …
Under a mild assumption, a mapping, which can be approximated by multi-layer neural …