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Innovative Migrants? Operators for Improved Genetic Optimization of Fuzzy Logic Controller

机译:创新移民?改进遗传算法的模糊逻辑控制器算子

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The Fuzzy Logic Controller (FLC) is very much useful in more complex situations which cannot be dealt mathematically. By providing the knowledge about the complex system, Fuzzy logic controller (FLC) can be developed and formed into a number of fuzzy rules. Since, FLC needs more human approach to control, Genetic algorithm is introduced for the purpose of the design and optimization of fuzzy rule base. But due to some problems like messy overlapping of membership functions and redundant rules, simple GA is not enough. To overcome the above situations, it is better to introduce the migrants? formation which is the movement of individuals between subpopulations. In this study, migrants are introduced in 3 populations (7×7, 5×5 and 3×3) for a second order process and verified the improvement in the genetic optimization of the process.
机译:模糊逻辑控制器(FLC)在无法数学处理的更复杂情况下非常有用。通过提供有关复杂系统的知识,可以开发模糊逻辑控制器(FLC)并将其形成为许多模糊规则。由于FLC需要更多的人为控制方法,因此引入遗传算法来设计和优化模糊规则库。但是由于一些问题,例如成员函数的混乱重叠和冗余规则,简单的GA是不够的。为了克服上述情况,最好引进移民吗?形成是个体在亚群之间的运动。在这项研究中,移民被引入了3个种群(7×7、5×5和3×3)以进行二阶过程,并验证了过程遗传优化的改进。

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