Robust estimation of arc length in a GMAW process by an adaptive extended Kalman filter

Abstract

An adaptive extended Kalman filter is designed to estimate the arc length in a gas metal arc welding system. The simulation results show that the estimated variables track the true variables of the non-linear model with negligible error and are robust against parameters uncertainties. The proposed estimator also operates adequately in a highly noisy welding environment. Because of the low computational requirements and little lag produced in the process dynamic, use of the proposed estimator would be valuable in the design of a controller for the gas metal arc welding system.