Abstract:
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.
