Gain tuning for high speed vibration control of a multilink flexible manipulator using artificial neural network

[+] Author and Article Information
Waweru Njeri

Gifushi Furuichiba 260-2 Koopo megumi 2-2 Gifu, Japan 501-1121 Japan waweru@ymail.com

Minoru Sasaki

1-1 Yanagido, Gifu Gifu, 501-1193 Japan sasaki@gifu-u.ac.jp

Kojiro Matsushita

1-1 Yanagido, Gifushi Gifu, Gifu-ken 501-1193 Japan kojirom@gifu-u.ac.jp

1Corresponding author.

Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the Journal of Vibration and Acoustics. Manuscript received January 11, 2019; final manuscript received March 13, 2019; published online xx xx, xxxx. Assoc. Editor: Huageng Luo.

ASME doi:10.1115/1.4043241 History: Received January 11, 2019; Accepted March 13, 2019


Flexible manipulators are associated with merits like low power consumption, use of small actuators, high speed and their low cost due to fewer materials requirements than their rigid counterparts. However, they suffer from link vibration which hinders the aforementioned merits from being realized. The limitations of link vibrations are time wastage, poor precision and the possibility of failure due to vibration fatigue. This paper extends the vibration control mathematical foundation from a single link manipulator to a 3D, two links flexible manipulator. The vibration control theory developed earlier feeds back a fraction of the link root strain to increase the system damping, thereby reducing the strain. This extension is supported by experimental results. Further improvements are proposed by tuning the right proportion of root strain to feed back, and the timing using artificial neural networks. The algorithm was implemented online in Matlab interfaced with dSPACE for practical experiments. From the practical experiment, done in consideration of a variable load, Neural network tuned gains exhibited a better performance over those obtained using fixed feedback gains in terms of damping of both torsional and bending vibrations and tracking of joint angles.

Copyright © 2019 by ASME
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