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A method of self-generating fuzzy rule base via genetic algorithm

机译:一种基于遗传算法的自生成模糊规则库的方法

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It is known that the fuzzy control rules for a control system is always built by designers with trial and error and based on their experience or some experiments. This paper introduces a genetic algorithm (GA) based method to generate a satisfactory fuzzy rule base spontaneously. With the specific structure of the chromosome, the special mutation operation and the adequate fitness function, the proposed method with GA produces a fuzzy rule base with small number of rules, suitable placement of the premise's fuzzy sets and proper location of the consequent singletons. The generated fuzzy rule base can be the controller in a closed loop system to achieve some control objective or can be a fuzzy model to approximate an unknown nonlinear system. Finally, two examples are illustrated to show the effectiveness of the proposed method on the fuzzy control design and fuzzy modeling respectively.
机译:众所周知,控制系统的模糊控制规则总是由设计者通过反复试验并根据他们的经验或一些实验来建立的。本文介绍了一种基于遗传算法的方法,可自动生成令人满意的模糊规则库。利用染色体的特定结构,特殊的突变操作和适当的适应度函数,所提出的遗传算法可以生成规则数量少,前提模糊集适当放置以及后续单例的正确位置的模糊规则库。生成的模糊规则库可以是闭环系统中的控制器来实现某些控制目标,也可以是模糊模型来近似未知的非线性系统。最后,通过两个例子说明了该方法在模糊控制设计和模糊建模中的有效性。

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