dc.contributor.author |
Njeri, Waweru |
|
dc.contributor.author |
Sasaki, Minoru |
|
dc.contributor.author |
Matsushita, Kojiro |
|
dc.date.accessioned |
2019-06-11T12:51:32Z |
|
dc.date.available |
2019-06-11T12:51:32Z |
|
dc.date.issued |
2018-06-05 |
|
dc.identifier.uri |
http://41.89.227.156:8080/xmlui/handle/123456789/891 |
|
dc.description.abstract |
Despite the numerous advantages associated with the flexible manipulators, link vibrations
stand in the way to reaping these benefits. This leads to time wastage waiting for vibrations to
decay to safe operating levels and the possibility of mechanical failure due to vibration fatigue.
This paper presents direct strain feedback vibration control by tuning the feedback gains using
artificial neural networks on a 3D flexible manipulator. Online backpropagation was developed in
MatLab Simulink and implemented in dSPACE environment for practical experiments. Results
show significant reduction in the link vibration relative to the performance of fixed feedback gain |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Proceedings of the 2018 JSME Conference on Robotics and Mechatronics, Kitakyushu, Japan |
en_US |
dc.subject |
Flexible manipulator, link vibrations, neural networks, strain feedback gain tuning |
en_US |
dc.title |
Strain feedback gain tuning using neural network for the vibration control in a multilink flexible manipulator |
en_US |
dc.type |
Article |
en_US |