Self-organizing fuzzy controller for the molten steel level control of a twin-roll strip casting process

Abstract

The twin-roll strip casting process is a steel-strip production method that combines continuous casting and hot rolling process in a single operation. The quality of strip casting process depends on many process parameters, such as molten steel level in the tundish, solidification position and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. Hence, it is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free control strategy is employed to overcome this problem. The self-organizing fuzzy control (SOFC) strategy is developed to control the molten steel level of a strip casting process. It has on-line learning ability and the rule tables can be modified automatically and continuously for responding to the system's nonlinear and time-varying behaviors. Since this model-free controller has simple control structure and small number of control parameters, it is easy to implement. Simulation results based on semi-experimental system dynamic model and parameters are executed to show the control performance of the proposed intelligent controller.