TY - JOUR
T1 - Tracking Control of a Miniature 2-DOF Manipulator with Hydrogel Actuators
AU - Doroudchi, Azadeh
AU - Khodambashi, Roozbeh
AU - Sharifzadeh, Mohammad
AU - Li, Dongting
AU - Berman, Spring
AU - Aukes, Daniel M.
N1 - Funding Information:
Manuscript received October 23, 2020; accepted February 20, 2021. Date of publication March 19, 2021; date of current version April 14, 2021. This letter was recommended for publication by Associate Editor O. Ozcan and Editor C. Laschi upon evaluation of the reviewers’ comments. This work was supported by Office of Naval Research (ONR) Award N00014-17-1-2117. (Azadeh Doroudchi and Roozbeh Khodambashi contributed equally to the work.) (Corresponding author: Daniel Aukes.) Azadeh Doroudchi is with the School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 USA (e-mail: adoroudc@asu.edu).
Funding Information:
Thisworkwas supported by Office ofNaval Research (ONR)Award N00014-17-1-2117.
Publisher Copyright:
© 2016 IEEE.
PY - 2021/7
Y1 - 2021/7
N2 - Due to the nature of the complex spatiotemporal dynamics of stimuli-responsive soft materials, closed-loop control of hydrogel-actuated mechanisms has remained a challenge. This letter demonstrates, for the first time, closed-loop trajectory tracking control in real-time of a millimeter-scale, two degree-of-freedom manipulator via independently-controllable, temperature-responsive hydrogel actuators. A linear state-space model of the manipulator is developed from input-output measurement data, enabling the straightforward application of control techniques to the system. The Normalized Mean Absolute Error (NMAE) between the modeled and measured displacement of the manipulator's tip is below 10%. We propose an Observer-based controller and a robust H-optimal controller and evaluate their performance in a trajectory tracking output-feedback framework, compared with and without sinusoidal disturbances and noise. We demonstrate in simulation that the H∞-optimal controller, which is computed using Linear Matrix Inequality (LMI) methods, tracks an elliptical trajectory more accurately than the Observer controller and is more robust to disturbances and noise. We also show experimentally that the H∞-optimal controller can be used to track different trajectories with an NMAE below 15\%, even when the manipulator is subject to a 3 g load, 12.5 times an actuator's weight. Finally, a payload transport scenario is presented as an exemplar application; we demonstrate that an array of four manipulators is capable of moving a payload horizontally by applying the proposed H∞-optimal trajectory-tracking controller to each manipulator in a decoupled manner.
AB - Due to the nature of the complex spatiotemporal dynamics of stimuli-responsive soft materials, closed-loop control of hydrogel-actuated mechanisms has remained a challenge. This letter demonstrates, for the first time, closed-loop trajectory tracking control in real-time of a millimeter-scale, two degree-of-freedom manipulator via independently-controllable, temperature-responsive hydrogel actuators. A linear state-space model of the manipulator is developed from input-output measurement data, enabling the straightforward application of control techniques to the system. The Normalized Mean Absolute Error (NMAE) between the modeled and measured displacement of the manipulator's tip is below 10%. We propose an Observer-based controller and a robust H-optimal controller and evaluate their performance in a trajectory tracking output-feedback framework, compared with and without sinusoidal disturbances and noise. We demonstrate in simulation that the H∞-optimal controller, which is computed using Linear Matrix Inequality (LMI) methods, tracks an elliptical trajectory more accurately than the Observer controller and is more robust to disturbances and noise. We also show experimentally that the H∞-optimal controller can be used to track different trajectories with an NMAE below 15\%, even when the manipulator is subject to a 3 g load, 12.5 times an actuator's weight. Finally, a payload transport scenario is presented as an exemplar application; we demonstrate that an array of four manipulators is capable of moving a payload horizontally by applying the proposed H∞-optimal trajectory-tracking controller to each manipulator in a decoupled manner.
KW - Modeling
KW - and learning for soft robots
KW - control
KW - soft robot applications
KW - soft robot materials and design
KW - soft sensors and actuators
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U2 - 10.1109/LRA.2021.3067622
DO - 10.1109/LRA.2021.3067622
M3 - Article
AN - SCOPUS:85103241841
SN - 2377-3766
VL - 6
SP - 4774
EP - 4781
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 3
M1 - 9382080
ER -