Box-Jenkins Model of Elastic Drive System Using Levenberg-Marquardt Algorithm
| dc.contributor.author | Jafari, Reza | en |
| dc.date.accessioned | 2025-02-05T13:21:39Z | en |
| dc.date.available | 2025-02-05T13:21:39Z | en |
| dc.date.issued | 2024-03-21 | en |
| dc.description.abstract | This paper explains the derivation of Box-Jenkins model for the elastic drive system using Levenberg-Marduardt algorithm. The Box-Jenkins model which is the most flexible linear model has been chosen to identify the elastic drive system. The GPAC analysis has been used for the preliminary identification and the Maximum Likelihood Estimator (Levenberg-Marduardt) is used for the parameter estimations. Several models have been developed for the elastic drive system and the simplest model has been chosen. The accuracy of the final model, residual analysis, has been checked using CHI-Square test. | en |
| dc.description.version | Accepted version | en |
| dc.format.extent | Pages 467-494 | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | https://doi.org/10.1007/978-3-031-53960-2_30 | en |
| dc.identifier.eissn | 2367-3389 | en |
| dc.identifier.isbn | 9783031539596 | en |
| dc.identifier.issn | 2367-3370 | en |
| dc.identifier.orcid | Jafari, Reza [0000-0002-4520-9305] | en |
| dc.identifier.uri | https://hdl.handle.net/10919/124500 | en |
| dc.identifier.volume | 919 LNNS | en |
| dc.language.iso | en | en |
| dc.publisher | Springer Nature | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.title | Box-Jenkins Model of Elastic Drive System Using Levenberg-Marquardt Algorithm | en |
| dc.title.serial | Lecture Notes in Networks and Systems | en |
| dc.type | Conference proceeding | en |
| dc.type.dcmitype | Text | en |
| dc.type.other | Conference Proceeding | en |
| pubs.organisational-group | Virginia Tech | en |
| pubs.organisational-group | Virginia Tech/Innovation Campus | en |