Self-Adjusting Model Algorithmic Control of a Three-Phase Electric Arc Furnace

An advanced control strategy, based on the principles of Self-Adjusting Model Algorithmic Control (SAMAC), for regulating the energy input to a nonlinear electric arc furnace system is presented in this paper. The SAMAC strategy is an extension of Model Algorithmic Control (MAC) designed to accommodate the nonlinear and time-varying characteristics of the arc furnace process. Simulation results show that SAMAC yields an improved performance over both the traditional MAC strategy and a conventional analog control system (typical of many existing furnace installations) in terms of commonly used classical measures of response characteristics, including speed of response, settling time, overshoot, cumulative error, and sensitivity to variations in plant parameter values (robustness).