Publication: Flex sensors precompensator via hammerstein-wiener modelling approach for improved automated goniometric measurements
| dc.contributor.author | Ali, Syed Afdar Ali Syed Mubarak | |
| dc.date.accessioned | 2024-01-18T03:00:41Z | |
| dc.date.available | 2024-01-18T03:00:41Z | |
| dc.date.issued | 2020-04-01 | |
| dc.description.abstract | This research introduces a new approach to model the characteristic of flex sensors on a goniometric glove, which is designed to capture the user hand gesture that can be used to control a bionic hand. The main technique employs a constrained control strategy which is aimed to provide an approximate linear mapping between the raw sensor output and the dynamic finger goniometry. In order to smoothly recover the goniometry on the bionic hand's side during the transmission, the precompensator is restructured into a Hammerstein-Wiener model, which contains of a linear dynamic system and two static nonlinearities. A series of real-time experiments involving several hand gestures have been conducted to analyse the performance of the proposed method. The performance is evaluated in terms of the integral of absolute error between the glove's and the bionic hand's dynamic goniometry. Comparisons are made with the raw sensor data, which has been preliminarily calibrated with the finger goniometry, and the Hammerstein-Wiener model. Experimental results show that the raw sensor data result in average percentage errors between 7.1% and 20.193%, whereas for the Wiener model, the average percentage errors vary between 2.8% and 3.32%, which are well below the range from the raw data. A clear error reduction is obtained via the Hammerstein-Wiener precompensator where the resulting average percentage errors are no greater than 1.53%. This concludes that the proposed strategy can remarkably improve the dynamic goniometry of the glove. | |
| dc.identifier.uri | https://erepo.usm.my/handle/123456789/18103 | |
| dc.language.iso | en | |
| dc.title | Flex sensors precompensator via hammerstein-wiener modelling approach for improved automated goniometric measurements | |
| dc.type | Resource Types::text::thesis | |
| dspace.entity.type | Publication | |
| oairecerif.author.affiliation | Universiti Sains Malaysia |