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

机译:铰接式机械手的模糊遗传控制器设计

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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.
机译:在这项研究中,设计了模糊逻辑控制器(FLC)来操纵铰接式机器人抓爪。通过优化新近引入的FLC隶属函数系数,利用遗传算法利用先前研究的想法来提高FLC的性能。拟议的控制器已应用于Simulink中的机器人抓手模型。总而言之,遗传算法能够在平均至少八(8)代之后得出最优化的参数,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。对于物理实现以及所利用遗传算法的可能改进,有必要进行进一步的研究。

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