机器人时变二次规划容噪归零神经网络的进一步研究

Proceedings of the 1st International Conference on Algorithms, Computing and Systems Pub Date : 2017-08-10 DOI:10.1145/3127942.3127956

Mei Liu, Shuai Li, Yinyan Zhang, Long Jin

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引用次数: 1

摘要

近年来，提出了一种改进的归零神经网络(MZNN)模型，用于求解二次规划问题，该模型具有抗噪声能力。在本文中，我们对该模型进行了进一步的研究，并提出了一个非线性函数激活模型。最后，将提出的非线性函数激活模型应用于机器人的运动控制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Further Investigations on Noise-Tolerant Zeroing Neural Network for Time-Varying Quadratic Programming with Robotic Applications

Recently, a modified zeroing neural network (MZNN) model has been presented for solving quadratic programming problems, which is of noise-tolerant ability. In this paper, we conduct further investigations on such a model and then present a nonlinear function activated model. Finally, the presented nonlinear function activated model is applied to the motion control of robots.

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Proceedings of the 1st International Conference on Algorithms, Computing and Systems

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