Strain feedback gain tuning using neural network for the vibration control in a multilink flexible manipulator

Njeri, Waweru; Sasaki, Minoru; Matsushita, Kojiro

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