Abstract : The aim of this contribution is to discuss suitability of extreme learning machine (ELM) approach for modeling multisource friction for motion control purposes. The specific features of multisource friction in mechatronic systems are defined, the main aspects of friction modeling by a standard ELM are investigated and some modifications are proposed to make it more suitable for specific demands of the discussed task. This allows to formulate some general remarks concerning properties of ELM for function approximation.
Richard Chbeir; Yannis Manolopoulos; Ilias Maglogiannis; Reda Alhajj. 11th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2015), Sep 2015, Bayonne, France. IFIP Advances in Information and Communication Technology, AICT-458, pp.318-333, 2015, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-23868-5_23〉
https://hal.inria.fr/hal-01385367
Contributeur : Hal Ifip
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Soumis le : vendredi 21 octobre 2016 - 11:43:24
Dernière modification le : mercredi 13 décembre 2017 - 15:36:01
Jacek Kabziński. Is Extreme Learning Machine Effective for Multisource Friction Modeling?. Richard Chbeir; Yannis Manolopoulos; Ilias Maglogiannis; Reda Alhajj. 11th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2015), Sep 2015, Bayonne, France. IFIP Advances in Information and Communication Technology, AICT-458, pp.318-333, 2015, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-319-23868-5_23〉. 〈hal-01385367〉
