基于模糊神经网络的水浴系统温度控制

B. Bhushan, Ajit Kumar Sharma, Deepti Singh
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引用次数: 1

摘要

传统的控制器通常需要事先了解过程的数学建模。数学建模的不准确性降低了过程的性能,特别是对于非线性和复杂的控制问题。为了克服上述困难,实现了模糊逻辑(FL)和自适应神经模糊推理系统(ANFIS)等智能控制器。模糊控制器被设计成与语言控制规则形式的知识一起工作。但是,将这些语言规则转化为模糊集理论的框架取决于某些参数的选择,而这些参数的选择尚无形式化方法。分析表明,ANFIS最适合于上述系统的自适应温度控制。与FLC相比,ANFIS产生稳定的控制信号。它具有更好的温度跟踪能力,几乎为零超调和最小的绝对误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy & ANFIS based temperature control of water bath system
Conventional controllers usually require a prior knowledge of mathematical modeling of the process. The inaccuracy of mathematical modeling degrades the performance of the process, especially for non-linear and complex control problem. To overcome above difficulties intelligent controllers like Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are implemented. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.
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