An electric furnace, inside which desired temperatures are kept constant by generating heat, is known to be a difficult system to control and model exactly because system parameters and response delay time are varied as the temperature and position are changed. In this study, the heating system of ceramic drying furnaces with time-varying parameters is mathematically modeled and control parameters are estimated by using a recursive least-square method. The generalized predictive control with exponential weight (GPCEW), which always guarantees the stability of closed loop systems and can be effectively applied to internally unstable systems, is employed in the temperature control of ceramic drying electric furnaces and its performances is experimentally verified. It is proven that temperature tracking of GPCEW is more stable than the generalized predictive control (GPC) and rapidly settles down by increasing the prediction horizon.

Keywords: SILICON-CARBIDE WHISKERS; RICE HULLS