Development of a piezoelectric-actuated drop-on-demand droplet generator using adaptive wavelet neural network control scheme

This paper presents the design, fabrication and control of a piezoelectric-type droplet generator which is applicable for on-line dispensing. The piezoelectric-actuated dispensing system consists of a linear piezoelectric motor (LPM) actuated table, a plastic syringe, a nozzle, a linear encoder and a PC-based control unit. Adaptive wavelet neural network (AWNN) control is applied to overcome nonlinear hysteresis inherited in the LPM. The adaptive learning rates are derived based on the Lyapunov stability theorem so that convergence of the tracking error can be assured. Unlike open-loop dispensing system, the system proposed can potentially generate droplets with high accuracy. Experimental verifications including regulating and tracking control are performed firstly to assure the reliability of the proposed control schemes. Real dispensing is then conducted to validate the feasibility of the piezoelectric-actuated drop-on-demand droplet generator. The results demonstrate that the proposed scheme works well in developing the piezoelectric-actuated drop-on-demand dispensing system.