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Adaptive PD fuzzy control with dynamic learning rate for two-wheeled balancing six degrees of freedom robotic arm

机译:具有动态学习率的两轮平衡六自由度机器人手臂的自适应PD模糊控制

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The paper proposes a novel method for enhanced fusion adaptive fuzzy control in the two-wheeled balancing six degrees of freedom robotic arm. The two-wheeled mobile robot system and six degrees of freedom robotic arm are integrated into the mobile robot system. Due to the motion of the robot arm, the stability issue becomes more complex. This study employs the adaptive fuzzy control to provide suitable controller for the mobile robot system. In addition, a dynamic learning rate can effectively improve the learning performance. In order to show the superiority of the proposed controller, this paper compares our proposed method with other control methods as proportional-derivative (PD) controller, fuzzy controller, adaptive fuzzy controller, PD fuzzy controller, and adaptive PD controller. The experiment results clearly demonstrate that the proposed control method has much faster convergent speed and is very well performed.
机译:提出了一种在两轮平衡六自由度机械臂中增强融合自适应模糊控制的新方法。两轮移动机器人系统和六个自由度机械臂集成到移动机器人系统中。由于机器人手臂的运动,稳定性问题变得更加复杂。本研究采用自适应模糊控制为移动机器人系统提供合适的控制器。另外,动态学习速率可以有效地提高学习性能。为了显示所提出的控制器的优越性,本文将我们提出的方法与其他控制方法进行了比较,例如比例微分(PD)控制器,模糊控制器,自适应模糊控制器,PD模糊控制器和自适应PD控制器。实验结果清楚地表明,所提出的控制方法收敛速度快得多,并且执行效果很好。

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