Молимо вас користите овај идентификатор за цитирање или овај линк до ове ставке: https://scidar.kg.ac.rs/handle/123456789/18804
Назив: Conceptual modeling of hysteresis in piezo crystals using neural networks
Аутори: Kelić, Lazar
Pršić, Dragan
Датум издавања: 2023
Сажетак: Piezoelectric materials are a subset of a larger class of materials known as ferroelectric materials. Ferroelectricity is the characteristic of certain materials that have a spontaneous electrical polarization that can be reversed by the application of an electric field. Like the magnetic equivalent (ferromagnetic materials), ferroelectric materials exhibit hysteresis loops based on the applied electric field and the history of that applied electric field. Hysteresis compensation is necessary wherever high precision positioning or piezo control of the mechanism is required. For forecasting purposes, of hysteresis, the Bouc-Ven model was most often used, and more recently, hysteresis modeling using neural networks has begun. The paper will show a way of conceptual predicting, and then for hysteresis, using a neural network.
URI: https://scidar.kg.ac.rs/handle/123456789/18804
Тип: conferenceObject
Налази се у колекцијама:Faculty of Mechanical and Civil Engineering, Kraljevo

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