Nested-list Approach for the Stageless Evaluation of a Vector Preisach Model based on Rotational Operators

Nierla M, Rupitsch S, Kaltenbacher M (2017)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2017

Pages Range: 491-496

Conference Proceedings Title: AMA Conferences 2017 – SENSOR 2017 and IRS2 2017

Event location: Nürnberg DE

DOI: 10.5162/sensor2017/D4.4

Abstract

The Everett function is a widely used tool to evaluate the output of scalar Preisach hysteresis
operators. Compared to a matrix-based implementation, the Everett function does not only allow a
stageless evaluation of the switching state but, furthermore, reduces the required storage to a single
list of dominant input minima and maxima. To deal with magnetic fields that change direction over
time, a vector extension of the scalar Preisach model based on rotational operators can be utilized.
This straight-forward extension enables an efficient description of vector hysteresis phenomena. Due
to the dependency between the newly added rotational operator and the original switching operator,
neither the usage of a single list nor the direct application of the Everett function is possible. In this
contribution, we propose a nested-list data structure for the vector Preisach model based on rotational
operators. Exploiting this data structure allows the usage of an adapted Everett function and, thus, an
efficient, stageless representation of both the rotational operator as well as the switching operator.

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How to cite

APA:

Nierla, M., Rupitsch, S., & Kaltenbacher, M. (2017). Nested-list Approach for the Stageless Evaluation of a Vector Preisach Model based on Rotational Operators. In AMA Conferences 2017 – SENSOR 2017 and IRS2 2017 (pp. 491-496). Nürnberg, DE.

MLA:

Nierla, Michael, Stefan Rupitsch, and Manfred Kaltenbacher. "Nested-list Approach for the Stageless Evaluation of a Vector Preisach Model based on Rotational Operators." Proceedings of the 18th International Conference on Sensors and Measurement Technology, Nürnberg 2017. 491-496.

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