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

机译:一种通过遗传算法自成模糊规则基础的方法

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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始终由设计人员构建,具有试验和错误,并根据他们的经验或一些实验。本文介绍了一种基于遗传算法(GA)的方法,用于自发地产生令人满意的模糊规则基础。利用染色体的具体结构,特殊突变操作和适当的健身功能,所提出的方法与GA产生具有少量规则的模糊规则基础,适当放置前提的模糊集和后果单身的正确位置。产生的模糊规则基础可以是闭环系统中的控制器,以实现一些控制目标,或者可以是近似一个未知的非线性系统的模糊模型。最后,示出了两个示例以分别显示所提出的方法在模糊控制设计和模糊建模上的有效性。

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