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.

中文翻译：

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一种改进的金属感应加热自整定模糊逻辑温度控制器

本文提出了一种建立与上升时间设置和最终目标温度相对应的动态目标曲线生成器的方法，作为用于金属加热过程应用的模糊逻辑控制器的参考。为了达到这个目标，模糊控制器中存在一些必须根据系统情况设置的量化因素，以及专家的经验会导致控制器缺乏适应性。为了解决这个问题，本文对所有量化因素进行了深入分析，并设计了一个自整定模块，使控制器能够根据系统情况进行实时调整，最终使其更自适应。在设计过程中，使用有限元分析进行比较传统模糊逻辑控制器和自调整模糊逻辑控制器 (STFLC) 的控制能力的模拟。最后，在感应加热系统上进行了实验，以验证所提出的 STFLC 的效果。结果表明，通过提出的自整定模块，控制器的控制能力和适应性得到了显着提高。