Data-driven modeling for electro-active liquid crystal polymer networks
Abstract In this paper, we propose a data-driven nonlinear modeling approach to describe the dynamics of smart surfaces composed of electroactive liquid crystal networks (LCNs). LCNs are among the top candidates for materials to be employed in smart surfaces such as haptic displays. To realize such...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-024-06441-9 |
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| _version_ | 1841544338246467584 |
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| author | Anahita Amiri Mohammad Fahim Shakib Ines Lopez Arteaga Nathan van de Wouw |
| author_facet | Anahita Amiri Mohammad Fahim Shakib Ines Lopez Arteaga Nathan van de Wouw |
| author_sort | Anahita Amiri |
| collection | DOAJ |
| description | Abstract In this paper, we propose a data-driven nonlinear modeling approach to describe the dynamics of smart surfaces composed of electroactive liquid crystal networks (LCNs). LCNs are among the top candidates for materials to be employed in smart surfaces such as haptic displays. To realize such applications, the ability to predict an accurate LCN surface response as a function of the input signal is crucial. In this paper, we propose a data-driven modeling approach to identify the parameters of a dynamic model based on experimental data. The resulting model is used for feedforward control to compute the appropriate excitation parameters that ensure a certain desired surface deformation. This feedforward control approach is validated in a simulation study. |
| format | Article |
| id | doaj-art-1d25843f860c475b90dba5b1c7f078e6 |
| institution | Kabale University |
| issn | 3004-9261 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-1d25843f860c475b90dba5b1c7f078e62025-01-12T12:35:09ZengSpringerDiscover Applied Sciences3004-92612025-01-017111510.1007/s42452-024-06441-9Data-driven modeling for electro-active liquid crystal polymer networksAnahita Amiri0Mohammad Fahim Shakib1Ines Lopez Arteaga2Nathan van de Wouw3Department of Mechanical Engineering, Eindhoven University of TechnologyDepartment of Electrical and Electronic Engineering, Imperial College LondonDepartment of Mechanical Engineering, Eindhoven University of TechnologyDepartment of Mechanical Engineering, Eindhoven University of TechnologyAbstract In this paper, we propose a data-driven nonlinear modeling approach to describe the dynamics of smart surfaces composed of electroactive liquid crystal networks (LCNs). LCNs are among the top candidates for materials to be employed in smart surfaces such as haptic displays. To realize such applications, the ability to predict an accurate LCN surface response as a function of the input signal is crucial. In this paper, we propose a data-driven modeling approach to identify the parameters of a dynamic model based on experimental data. The resulting model is used for feedforward control to compute the appropriate excitation parameters that ensure a certain desired surface deformation. This feedforward control approach is validated in a simulation study.https://doi.org/10.1007/s42452-024-06441-9Liquid Crystal Networks (LCNs)Nonlinear system identificationData-driven modelingDynamic modelsNonlinear feedforward controlElectro-active coatings |
| spellingShingle | Anahita Amiri Mohammad Fahim Shakib Ines Lopez Arteaga Nathan van de Wouw Data-driven modeling for electro-active liquid crystal polymer networks Discover Applied Sciences Liquid Crystal Networks (LCNs) Nonlinear system identification Data-driven modeling Dynamic models Nonlinear feedforward control Electro-active coatings |
| title | Data-driven modeling for electro-active liquid crystal polymer networks |
| title_full | Data-driven modeling for electro-active liquid crystal polymer networks |
| title_fullStr | Data-driven modeling for electro-active liquid crystal polymer networks |
| title_full_unstemmed | Data-driven modeling for electro-active liquid crystal polymer networks |
| title_short | Data-driven modeling for electro-active liquid crystal polymer networks |
| title_sort | data driven modeling for electro active liquid crystal polymer networks |
| topic | Liquid Crystal Networks (LCNs) Nonlinear system identification Data-driven modeling Dynamic models Nonlinear feedforward control Electro-active coatings |
| url | https://doi.org/10.1007/s42452-024-06441-9 |
| work_keys_str_mv | AT anahitaamiri datadrivenmodelingforelectroactiveliquidcrystalpolymernetworks AT mohammadfahimshakib datadrivenmodelingforelectroactiveliquidcrystalpolymernetworks AT ineslopezarteaga datadrivenmodelingforelectroactiveliquidcrystalpolymernetworks AT nathanvandewouw datadrivenmodelingforelectroactiveliquidcrystalpolymernetworks |