LWR4+机械手自适应控制与神经网络控制的比较：仿真研究

IF 1.2 Q3 ENGINEERING, MECHANICAL

Archive of Mechanical Engineering Pub Date : 2023-11-06 DOI:10.24425/AME.2020.131686

Łukasz Woliński

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引用次数: 1

摘要

本文讨论了两种利用模型参数学习的控制算法。对自适应控制技术和人工神经网络控制技术进行了比较。两种控制算法分别在MATLAB和Simulink环境下实现，并应用于lwr4 +机械手在未知扰动下的位置控制仿真。实验结果表明，该人工神经网络控制器具有较好的控制性能。讨论了两种控制器的优缺点。讨论了学习算法对LWR 4+机器人控制的有效性。报道了两种lwr4 +机器人的动力学特性的初步实验。

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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Comparison of the adaptive and neural network control for LWR 4+ manipulators: simulation study

This paper deals with two control algorithms which utilize learning of their models’ parameters. An adaptive and artificial neural network control techniques are described and compared. Both control algorithms are implemented in MATLAB and Simulink environment, and they are used in the simulation of a postion control of the LWR 4+ manipulator subjected to unknown disturbances. The results, showing the better performance of the artificial neural network controller, are shown. Advantages and disadvantages of both controllers are discussed. The usefulness of the learning algorithms for the control of LWR 4+ robots is discussed. Preliminary experiments dealing with dynamic properties of the two LWR 4+ robots are reported.

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来源期刊

Archive of Mechanical Engineering ENGINEERING, MECHANICAL-

CiteScore

1.70

自引率

14.30%

发文量

审稿时长

15 weeks

期刊介绍： Archive of Mechanical Engineering is an international journal publishing works of wide significance, originality and relevance in most branches of mechanical engineering. The journal is peer-reviewed and is published both in electronic and printed form. Archive of Mechanical Engineering publishes original papers which have not been previously published in other journal, and are not being prepared for publication elsewhere. The publisher will not be held legally responsible should there be any claims for compensation. The journal accepts papers in English.