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A Simplified Version of Mamdani's Fuzzy Controller: The Natural Logic Controller

机译:Mamdani模糊控制器的简化版本:自然逻辑控制器

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This paper proposes the natural logic controller (NLC) that it comes through a very important simplification of the Mamdani's fuzzy controller (MFC) allowing easy-design for single-input-single-output (SISO) regulation problems. Usually, fuzzy controllers are built with two classical signals of process: The error and its rate of change. They use a moderate number of fuzzy subsets and fuzzy rules. The main features of the NLC approach are that use the minimal fuzzy partition (only two fuzzy subsets per variable) and it use the minimal fuzzy rule base (only two rules). The nonlinear resulting fuzzy controller is the simplest one with an analytically well-defined, input-output mapping and accepting a linear approximation at origin. It allows easy extension to more than two signals of process. Some properties of nonlinear mapping of NLC are analyzed and some results are also presents on testing stability when NLC is used on a linear process. A special attention is addressed to the two inputs NLC case, where stability can be tested using the circle criterion. Finally, two application examples are discussed in details.
机译:本文提出了自然逻辑控制器(NLC),它是通过对Mamdani的模糊控制器(MFC)进行的非常重要的简化而实现的,从而可以轻松设计单输入单输出(SISO)调节问题。通常,模糊控制器是用两个经典的过程信号构建的:误差及其变化率。他们使用中等数量的模糊子集和模糊规则。 NLC方法的主要特征是使用最小模糊分区(每个变量仅两个模糊子集),并且使用最小模糊规则库(仅两个规则)。非线性合成模糊控制器是最简单的一种,具有分析明确,输入输出映射并在原点接受线性近似的功能。它允许轻松扩展到两个以上的过程信号。分析了NLC的非线性映射的一些特性,并且在线性过程中使用NLC时,还给出了有关测试稳定性的一些结果。特别注意两个输入NLC的情况,可以使用圆准则来测试稳定性。最后,详细讨论了两个应用示例。

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