Design and performance evaluation of an exponentially weighted moving average–based adaptive control for piezo-driven motion platform

Abstract

In this article, building a controlled system with velocity feedback in the inner loop for a platform driven by piezoelectric motors is investigated. Such a motion control system is subject to disturbance such as friction, preload, and temperature rise in operation. Especially, temperature rise is an essential problem of using piezoelectric motor, but very few research works address this topic in depth. Exponentially weighted moving average method has been widely used in process control to deal with systematic change and drift disturbance. It is attempted to map the exponentially weighted moving average method and the predictor corrector control with two exponentially weighted moving average formulas into a run-to-run model reference adaptive system for velocity control. Using a predictive friction model, a dead-zone compensator is built that can reduce the friction effect and provide an approximately linear relation of the input voltage and the output velocity for the subsequent exponentially weighted moving average or predictor corrector control control design. Comparison of the exponentially weighted moving average, predictor corrector control, and proportional–integral–derivative controllers is carried out in experiment with different speed patterns on a single-axis and a bi-axial platform. The results indicate that the proposed run-to-run-model reference adaptive system predictor corrector control is superior to the other methods.