This paper presents a method to build a dynamic target curve producer corresponding to the rising time setting and the ultimate target temperature as a reference for a fuzzy logic controller that is used in the metal heating process application. To achieve this goal, there are some quantization factors in a fuzzy controller that must be set according to the system situation, as well as the experience of experts that will cause the controller to have a lack of adaptivity. To solve this problem, in this paper, all the quantization factors are analyzed thoroughly, and a self-tuning module is designed to make it possible for the controller to perform real-time adjustments based on the system situation and, eventually, make it more adaptive. During the design process, a simulation comparing the control capabilities of the conventional fuzzy logic controller and the self-tuning fuzzy logic controller (STFLC) is made using a finite element analysis. Finally, experiments are carried out on the induction heating system to verify the effect of the proposed STFLC. The results show that, with the proposed self-tuning module, the control capability and adaptivity of the controller were drastically improved.
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