Flexible manipulators are associated with merits such as 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 hinder 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 three-dimensional, 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.

Conventional rigid actuators, such as DC servo motors, face challenges in utilizing them in artificial muscles and soft robotics. Dielectric elastomer actuators (DEAs) overcome all these limitations, as they exhibit complex and fast motions, quietness, lightness, and softness. Recently, there has been much focus on studies of the DEAs material’s non-linearity, the non-linear electromechanical coupling, and viscoelastic behavior of VHB and silicone-based conical DEAs having compliant electrodes that are based on graphite powder and carbon grease. However, the mitigation of overshoot that arises from fast response conical DEAs made with solid electrodes has not received much research focus. In this paper, we fabricated a conical configuration of multi-walled carbon nanotube/polydimethylsiloxane (MWCNT/PDMS) based DEAs with a rise time of 10 ms, and 50% peak overshoot. We developed a full feedback state-based linear-quadratic regulator (LQR) having Luenberger observer to mitigate the DEAs overshoot in both the voltage ON and OFF instances. The cone DEA’s model was identified and a stable and well-fitting transfer function with a fit of 94% was obtained. Optimal parameters Q = 70,000, R = 0.1, and Q = 7000, R = 0.01 resulted in the DEA response having a rise time value of 20 ms with zero overshoot, in both simulations and experiments. The LQR approach can be useful for the control of fast response DEAs and this would expand the potential use of the DEAs as artificial muscles in soft robotics.