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机器人操纵器的自适应分数阶固定时间滑模控制设计

Design of Adaptive Fractional-Order Fixed-Time Sliding Mode Control for Robotic Manipulators.

作者信息

Ahmed Saim, Azar Ahmad Taher, Tounsi Mohamed

机构信息

College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia.

Automated Systems and Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh 11586, Saudi Arabia.

出版信息

Entropy (Basel). 2022 Dec 16;24(12):1838. doi: 10.3390/e24121838.

DOI:10.3390/e24121838
PMID:36554243
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9778649/
Abstract

In this investigation, the adaptive fractional-order non-singular fixed-time terminal sliding mode (AFoFxNTSM) control for the uncertain dynamics of robotic manipulators with external disturbances is introduced. The idea of fractional-order non-singular fixed-time terminal sliding mode (FoFxNTSM) control is presented as the initial step. This approach, which combines the benefits of a fractional-order parameter with the advantages of NTSM, gives rapid fixed-time convergence, non-singularity, and chatter-free control inputs. After that, an adaptive control strategy is merged with the FoFxNTSM, and the resulting model is given the label AFoFxNTSM. This is done in order to account for the unknown dynamics of the system, which are caused by uncertainties and bounded external disturbances. The Lyapunov analysis reveals how stable the closed-loop system is over a fixed time. The pertinent simulation results are offered here for the purposes of evaluating and illustrating the performance of the suggested scheme applied on a PUMA 560 robot.

摘要

在本研究中，针对具有外部干扰的机器人机械臂不确定动力学，引入了自适应分数阶非奇异固定时间终端滑模（AFoFxNTSM）控制。分数阶非奇异固定时间终端滑模（FoFxNTSM）控制的思想作为第一步被提出。这种方法结合了分数阶参数的优点和非奇异终端滑模的优点，实现了快速固定时间收敛、非奇异性和无抖振控制输入。之后，将自适应控制策略与FoFxNTSM相结合，得到的模型被标记为AFoFxNTSM。这样做是为了考虑由不确定性和有界外部干扰引起的系统未知动力学。李雅普诺夫分析揭示了闭环系统在固定时间内的稳定性。这里给出了相关的仿真结果，用于评估和说明所提出的方案应用于PUMA 560机器人时的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/8104e0189cb4/entropy-24-01838-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/44a1ce7e3c48/entropy-24-01838-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/a60802e92950/entropy-24-01838-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/5474b6842ca5/entropy-24-01838-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/09ad44d07a67/entropy-24-01838-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/17ea810d9973/entropy-24-01838-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/b42094e531f6/entropy-24-01838-g010.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/82cfe1360f76/entropy-24-01838-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/ae0ce9ccdebc/entropy-24-01838-g003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/a60802e92950/entropy-24-01838-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/5474b6842ca5/entropy-24-01838-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/09ad44d07a67/entropy-24-01838-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/17ea810d9973/entropy-24-01838-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/b42094e531f6/entropy-24-01838-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/26ecabe7d134/entropy-24-01838-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/914d/9778649/8104e0189cb4/entropy-24-01838-g012.jpg

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