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Robust Fuzzy Neural Network for Concrete Delivery Manipulator with Nonsingleton Input

机译:鲁棒模糊神经网络用于混凝土交付机械手与非荷车输入

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The control of the concrete manipulator is a challenge, considering its highly nonlinearity and coupling and the uncertainty from the internal and the external, which will effect the efficiency directly. In this paper, the kinemics and dynamics of the whole concrete delivery manipulator are analyzed firstly. An advanced control strategy, nonsingleton fuzzy neural network, is utilized on concrete delivery manipulator for the first time. Then the simulation study is conducted based the Simulink. It can be found that the establishment of dynamic model is appropriate and the proposed NSFNN controller can follow the target signal better. The result shows that the NSFNN controller can solve the uncertainty to some extent in the constrain of the frame of the type-1 logic fuzzy control.
机译:考虑其高度非线性和耦合以及内部和外部的耦合以及不确定性,控制混凝土操纵器是一项挑战,这将直接影响效率。在本文中,首先分析了整个混凝土输送机械手的运动学和动态。第一次在混凝土输送机械手上使用先进的控制策略。然后,基于Simulink进行仿真研究。可以发现,动态模型的建立是合适的,所提出的NSFNN控制器可以更好地遵循目标信号。结果表明,NSFNN控制器可以在一定程度上解决1型逻辑模糊控制的帧的某种程度的不确定性。

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