We propose to use an approach based on fuzzy logic for the adaptation of gap generation and mutation probability in a genetic algorithm. The performance of this method is presented with the benchmark problem of flight control and results show how it can decrease the error during the flight of an airplane using fuzzy logic for some parameters of the genetic algorithm. In this case of study, we use fuzzy systems for adapting two parameters of the genetic algorithm to improve the design of a type 2 fuzzy controller and enhance its performance to achieve flight control. Finally, a statistical test is presented to prove the performance enhancement in the application using fuzzy adaptation in the genetic algorithm. It is important to mention that not only is this idea for control problems but also it can be used in pattern recognition and many different problems.

中文翻译：

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2型模糊控制器遗传优化中间隙生成和变异的模糊动态自适应

我们建议使用一种基于模糊逻辑的方法来适应遗传算法中的缺口产生和突变概率。将该方法的性能与飞行控制的基准问题相结合，结果表明，对于遗传算法的某些参数，使用模糊逻辑可以降低飞机在飞行过程中的误差。在本研究案例中，我们使用模糊系统来适应遗传算法的两个参数，从而改进2型模糊控制器的设计并增强其性能以实现飞行控制。最后，提出了一种统计测试，以证明使用遗传算法中的模糊自适应可以提高应用程序的性能。