A novel three-finger IPMC gripper for microscale applications

Date

2007-09-17

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Publisher

Texas A&M University

Abstract

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 ???? 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-????m) 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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