Design of a Fuzzy-Genetic Controller for an Articulated Robot Gripper

Jason L. Española, A. Bandala, R. R. Vicerra, E. Dadios
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引用次数: 5

Abstract

In this study, a fuzzy logic controller (FLC) was designed to manipulate an articulated robot gripper. An idea from a previous study was utilized to enhance the performance of the FLC using genetic algorithms by optimizing newly-introduced coefficients in the membership functions of the FLC. The proposed controller was applied on a robot gripper model in Simulink. All in all, the genetic algorithm was able to come up with optimized parameters after an average of at least eight (8) generations and the proposed controller was able to follow the reference trajectory more accurately than the simple fuzzy controller. Further research will be necessary for physical implementation and possible improvement of the utilized genetic algorithm.
铰接式机器人夹持器的模糊遗传控制器设计
在本研究中,设计了一个模糊逻辑控制器(FLC)来操纵关节机器人的夹持器。利用前人研究的思想,利用遗传算法优化FLC的隶属函数中新引入的系数,提高FLC的性能。在Simulink中,将所提出的控制器应用于机器人夹持器模型。总而言之,遗传算法能够在平均至少八(8)代后得到优化参数,并且所提出的控制器能够比简单的模糊控制器更准确地遵循参考轨迹。对于所使用的遗传算法的物理实现和可能的改进,需要进一步的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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