Building an EDM Process Model by an Instrumental Variable Approach

Abstract

An electrical discharge machining (EDM) process model is critical in control system for stabilizing machining process and improving productivity. A two order AR model was firstly proposed for the process, but the deduced formulation of the model parameter estimates is proved biased. An instrumental variable approach is then proposed to correct the biased estimates. This approach was completed by two interactive Kalman filters. One filter provides instrumental variables, namely gap state estimates, through the latest estimated parameters; while the other uses the gap state estimates to recursively estimate a two order auto- regressive (AR) model parameters. The two Kalman filters by way of interactively supporting each other forms a new feasible way of online modeling an EDM process.