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Optimization of granulation for fuzzy controllers of autonomous mobile robots using the Firefly Algorithm

机译:使用Firefly算法的自主移动机器人模糊控制器的颗粒优化

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This paper describes a methodology based on optimal granularity allocation for fuzzy system design, and the main contribution is a method, based on the Firefly Algorithm, to generate and test information granules for fuzzy controllers of autonomous mobile robots. The Firefly Algorithm automatically generates and tests these granules which are defined by the parameter values of the membership functions, which are evaluated based on simulations of the robot plant and the final result is an ideal combination of information granules. The evaluation is made with a comparison of the actual trajectory generated by the fuzzy controller of the robot with respect to the desired path. To verify that the obtained results are significantly better, a statistical test is performed between the firefly and the genetic algorithms.
机译:本文介绍了一种基于最优粒度分配的模糊系统设计方法,其主要贡献是基于Firefly算法的一种用于生成和测试自主移动机器人模糊控制器信息颗粒的方法。 Firefly算法自动生成并测试由隶属函数的参数值定义的这些颗粒,这些成员值是根据机器人工厂的模拟进行评估的,最终结果是信息颗粒的理想组合。通过比较机器人的模糊控制器相对于所需路径生成的实际轨迹进行评估。为了验证所获得的结果明显更好,在萤火虫和遗传算法之间进行了统计检验。

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