In this article, a mechatronic system to compensate for the effect of hardware dynamics and achieve rapid resonance identification for an ultrasonic-vibration-assisted microforming system is developed. Recently, micromachining technology, including microforming, microjoining, and micropunching, has attracted great interests due to the need of miniaturized manufacturing system in emerging applications. It has been demonstrated that significant benefits such as reduction of input energy and prolongation of tool life can be gained by introducing ultrasonic vibration into the micromachining process, particularly when the vibration is maintained at the resonant frequency of the vibrating workpiece. However, the fundamental mechanism of ultrasonic vibration effect during the micromachining process has not yet been understood; the electrical actuators currently used to generate the ultrasonic vibration are bulky and not suitable for miniaturization of the micromachining system; and the control of ultrasonic vibration is primitive and far from being optimal. Motivated by these challenges, a microforming platform based on magnetostrictive actuator has been developed recently. Based on this microforming experiment platform, the main contributions of this article are two folds: (1) the use of a novel iterative learning control technique along with a vibration oscillation regulation circuit to compensate for the effect of the magnetostrictive actuator dynamics on the ultrasonic vibration generation, and thereby maintain the same vibration amplitude across a large excitation frequency range, and (2) the use of the Fibonacci search algorithm to achieve rapid online identification of the resonant frequency. Experimental results obtained from the developed magnetostrictive-based microforming platform are presented and discussed to demonstrate the proposed approach.

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