Model-Based Control of Electroslag Remelting Process Using Unscented Kalman Filter

Abstract

Electroslag remelting (ESR) is used widely throughout the specialty metals industry. The process generally consists of a regularly shaped electrode, wherein a small amount is immersed in liquid slag at a temperature higher than the melting temperature of the electrode. Melting droplets from the electrode fall through the lower density slag into a liquid pool constrained by a crucible and solidify into an ingot. High quality ingots require that electrode melt rate and immersion depth be controlled at all times during the process. This can be difficult when process conditions are such that the temperature distribution in the electrode is not at steady state. This condition is encountered during the beginning and closing stages of the ESR process and also during some process disturbances such as when the melt zone passes through a transverse electrode crack. To address these transient melting situations, a new method of the ESR estimation and control has been developed that incorporates an accurate, reduced order melting model to continually estimate the temperature distribution in the electrode. The ESR process is highly nonlinear, noisy, and has coupled dynamics. An extended Kalman filter and an unscented Kalman filter were chosen as possible estimators and compared in the controller design. During the highly transient periods in melting, the unscented Kalman filter showed superior performance for estimating and controlling the system.