Spatio-temporal modeling for overactuated motion control

Increasingly stringent performance requirements for motion systems necessitate explicit control of the flexible dynamic behavior. The aim of this paper is to present an approach to identify spatio-temporal models of overactuated mechatronic systems with a limited number of spatially distributed sensors. The proposed approach exploits the modal modeling framework and exploits the symmetry in modal models to enhance the spatial resolution of the identified spatially-sampled modal models. Spatio-temporal models are identified by updating prior finite element method-based models based on the identified extended modal models. The experimental results illustrate the effectiveness of the proposed approach for the identification of complex position-dependent mechanical systems.

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Publication Details

Journal
Mechatronics
Published
2024-11-20
DOI
https://doi.org/10.1016/j.mechatronics.2024.103270
Citations
3
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
0.75

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Spatio-temporal modeling for overactuated motion control

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Spatio-temporal modeling for overactuated motion control

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Abstract

Increasingly stringent performance requirements for motion systems necessitate explicit control of the flexible dynamic behavior. The aim of this paper is to present an approach to identify spatio-temporal models of overactuated mechatronic systems with a limited number of spatially distributed sensors. The proposed approach exploits the modal modeling framework and exploits the symmetry in modal models to enhance the spatial resolution of the identified spatially-sampled modal models. Spatio-temporal models are identified by updating prior finite element method-based models based on the identified extended modal models. The experimental results illustrate the effectiveness of the proposed approach for the identification of complex position-dependent mechanical systems.

MechatronicsVol. 105
Netherlands Organisation for Applied Scientific Research (NL), Eindhoven University of Technology (NL), ASML (Netherlands) (NL), Delft University of Technology (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 27%
Advanced Vision and Imaging
0.75
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