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首页> 外文期刊>International Journal of Advanced Robotic Systems >Robot manipulator identification based on adaptive multiple-input and multiple-output neural model optimized by advanced differential evolution algorithm:
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Robot manipulator identification based on adaptive multiple-input and multiple-output neural model optimized by advanced differential evolution algorithm:

机译:基于高级差分进化算法优化的自适应多输入多输出神经模型的机器人操纵器辨识:

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This article proposes a novel advanced differential evolution method which combines the differential evolution with the modified back-propagation algorithm. This new proposed approach is applied to train an adaptive enhanced neural model for approximating the inverse model of the industrial robot arm. Experimental results demonstrate that the proposed modeling procedure using the new identification approach obtains better convergence and more precision than the traditional back-propagation method or the lonely differential evolution approach. Furthermore, the inverse model of the industrial robot arm using the adaptive enhanced neural model performs outstanding results.
机译:本文提出了一种新颖的高级差分进化方法,该方法将差分进化与改进的反向传播算法相结合。该新提出的方法用于训练自适应增强神经模型,以近似工业机器人手臂的逆模型。实验结果表明,与传统的反向传播方法或孤独差分演化方法相比,使用新的识别方法提出的建模过程具有更好的收敛性和精度。此外,使用自适应增强型神经模型的工业机器人手臂的逆模型表现出色。

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