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不确定非线性死区输入机器人的自适应模糊控制器设计。

Adaptive Fuzzy Controller Design for Uncertain Robotic Manipulators Subject to Nonlinear Dead Zone Inputs.

机构信息

Zhengzhou Preschool Education College, Zhengzhou 450099, China.

出版信息

Comput Intell Neurosci. 2022 Sep 20;2022:9173249. doi: 10.1155/2022/9173249. eCollection 2022.

DOI:10.1155/2022/9173249
PMID:36177315
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9514920/
Abstract

This paper comes up with the adaptive fuzzy scheme for multi-degree robotic manipulators with dead zone. Fuzzy logic system is employed to approximate unknown nonlinear functions and input nonlinear functions with dead zones that are introduced. The adaptive fuzzy technique is utilized to deal with the problems of multi-joint robotic manipulators with unknown nonlinear functions in dead zones. Based on Lyapunov criterion, all the states and signals involved in the system are maintained in a certain bounded region and the tracking error converges to a small domain of origin. Finally, a simulation example of robotic manipulators with two joints is structured to confirm the practicability of the raised scheme.

摘要

本文针对具有死区的多自由度机器人提出了自适应模糊方案。模糊逻辑系统用于逼近未知的非线性函数和引入的具有死区的输入非线性函数。自适应模糊技术用于处理具有未知非线性函数的多关节机器人在死区内的问题。基于 Lyapunov 准则，系统中涉及的所有状态和信号都保持在一定的有界区域内，并且跟踪误差收敛到原点的小区域。最后，构建了一个具有两个关节的机器人的仿真示例，以确认所提出方案的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/5ce1dc5cc61c/CIN2022-9173249.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/a5fadbf1aaa2/CIN2022-9173249.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/3cc73869970e/CIN2022-9173249.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/a44e5a9c3a7a/CIN2022-9173249.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/5ce1dc5cc61c/CIN2022-9173249.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/a5fadbf1aaa2/CIN2022-9173249.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/3cc73869970e/CIN2022-9173249.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/a44e5a9c3a7a/CIN2022-9173249.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd3c/9514920/5ce1dc5cc61c/CIN2022-9173249.004.jpg

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本文引用的文献

1
Model free adaptive control of the under-actuated robot manipulator with the chaotic dynamics.具有混沌动力学的欠驱动机器人机械臂的无模型自适应控制
ISA Trans. 2021 Dec;118:106-115. doi: 10.1016/j.isatra.2021.02.006. Epub 2021 Feb 8.
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Adaptive Neural Network Tracking Control for Robotic Manipulators With Dead Zone.具有死区的机器人机械手的自适应神经网络跟踪控制。
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Decentralized adaptive fuzzy control of robot manipulators.
机器人操纵器的分布式自适应模糊控制
IEEE Trans Syst Man Cybern B Cybern. 1998;28(1):47-57. doi: 10.1109/3477.658577.
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