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A novel three-finger IPMC gripper for microscale applicationsYun, Kwan Soo 17 September 2007 (has links)
Smart materials have been widely used for control actuation. A robotic hand can
be equipped with artificial tendons and sensors for the operation of its various joints
mimicking human-hand motions. The motors in the robotic hand could be replaced with
novel electroactive-polymer (EAP) actuators. In the three-finger gripper proposed in this
paper, each finger can be actuated individually so that dexterous handling is possible,
allowing precise manipulation.
In this dissertation, a microscale position-control system using a novel EAP is
presented. A third-order model was developed based on the system identification of the
EAP actuator with an AutoRegresive Moving Average with eXogenous input (ARMAX)
method using a chirp signal input from 0.01 Hz to 1 Hz limited to 7 ñ V. With the
developed plant model, a digital PID (proportional-integral-derivative) controller was
designed with an integrator anti-windup scheme. Test results on macro (0.8-mm) and
micro (50-üm) step responses of the EAP actuator are provided in this dissertation and its
position tracking capability is demonstrated. The overshoot decreased from 79.7% to 37.1%, and the control effort decreased by 16.3%. The settling time decreased from 1.79
s to 1.61 s. The controller with the anti-windup scheme effectively reduced the
degradation in the system performance due to actuator saturation. EAP microgrippers
based on the control scheme presented in this paper will have significant applications
including picking-and-placing micro-sized objects or as medical instruments.
To develop model-based control laws, we introduced an approximated linear
model that represents the electromechanical behavior of the gripper fingers. Several chirp
voltage signal inputs were applied to excite the IPMC (ionic polymer metal composite)
fingers in the interesting frequency range of [0.01 Hz, 5 Hz] for 40 s at a sampling
frequency of 250 Hz. The approximated linear Box-Jenkins (BJ) model was well matched
with the model obtained using a stochastic power-spectral method. With feedback control,
the large overshoot, rise time, and settling time associated with the inherent material
properties were reduced. The motions of the IPMC fingers in the microgripper were
coordinated to pick, move, and release a macro- or micro-part. The precise manipulation
of this three-finger gripper was successfully demonstrated with experimental closed-loop
responses.
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