Abstract

It is well known that the casting and rolling processes of strip casting are integrated into a single production step for the manufacture of thin steel strips directly from molten metal. The quality of the strip casting process depends on many process parameters, such as the level of molten steel in the pool, solidification position, and roll gap. Their dynamic relationships are complex and the strip casting process has non-linear uncertainty and time-varying characteristics, so it is difficult to establish an accurate process model for designing a model-based controller to monitor strip quality. Here, a model-free adaptive fuzzy sliding-mode controller, which combines an adaptive rule with fuzzy and sliding-mode control, is proposed to monitor the level of molten metal. The proposed control strategy has online learning ability for responding to the system's non-linear and time-varying behaviours during control of the molten steel level. Since this model-free controller has a simple control structure and a small number of control parameters, it is easy to implement. Simulation results based on the dynamic model and parameters of a semi-experimental system are executed to show the control performance of the proposed intelligent controller.

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