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

机译:铰接式机器人夹具模糊遗传控制器的设计

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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:在该研究中,设计了一种模糊逻辑控制器(FLC)以操纵铰接式机器人夹具。通过先前研究的一个想法利用通过优化FLC的隶属函数中的新引入系数来增强FLC的性能使用遗传算法。所提出的控制器应用于Simulink的机器人夹具模型。总而言之,遗传算法能够在平均至少8(8)代之后提出优化参数,并且所提出的控制器能够比简单的模糊控制器更精确地遵循参考轨迹。进一步的研究对于物理实施以及采用遗传算法的可能改进是必要的。

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