Fractional-Order Nonsingular Terminal Sliding Mode Control of Uncertain Robot Neural Network

Weihai Zhang, Jianguo Guo, Zunjie Yu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Aiming at the problem of low tracking accuracy and slow convergence speed of robot trajectory tracking control system with uncertainties and external disturbances, an adaptive fractional-order fast terminal sliding mode controller based on radial basis function (RBF) neural network is proposed. First of all, the method adopts nonsingular fast terminal sliding mode control, which makes the system converge to the equilibrium point in a limited time, and uses the fractional-order controller to improve the tracking performance of the controller. Moreover, we use RBF neural network to approximate unknown non-linear function of the system, and combine with adaptive compensation mechanism to realize model-free control. The stability of the closed-loop system is proved by the Lyapunov stability theorem. Finally, taking the manipulator as an example to verify the theory. The simulation results show that the proposed method can improve the tracking performance and system convergence speed, enhance the robustness to modeling errors and external disturbances, and weaken the chattering generated by the system.

Original languageEnglish
Title of host publicationProceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4584-4589
Number of pages6
ISBN (Electronic)9781728158549
DOIs
StatePublished - Aug 2020
Externally publishedYes
Event32nd Chinese Control and Decision Conference, CCDC 2020 - Hefei, China
Duration: 22 Aug 202024 Aug 2020

Publication series

NameProceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020

Conference

Conference32nd Chinese Control and Decision Conference, CCDC 2020
Country/TerritoryChina
CityHefei
Period22/08/2024/08/20

Keywords

  • Fractional-Order Sliding Mode Control
  • RBF Neural Network
  • Trajectory Tracking
  • Uncertain Robot

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