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Fixed-Time Sliding Mode Control for Air-Floating Robot Using Actor-Critic Learning Structure

  • Harbin Institute of Technology
  • School of New Energy, Harbin Institute of Technology Weihai
  • Shanghai Aerospace Control Technology Institute
  • Aerospace System Engineering Shanghai

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

Abstract

A fixed-time sliding mode controller is developed for the three-degree-of-freedom air-floating robot (AFR) in the presence of model uncertainties and external disturbances. By dynamics transformation, the complex nonlinear AFR dynamics are transformed into a second-order feedback decoupling model. A neural network enhanced by actor-critic learning structure is designed to handle model uncertainties, and the nonsingular fast terminal sliding mode controller can ensure all signals in the closed-loop system converge to a residual set around the origin within a fixed time. The system stability is proved by Lyapunov theory and the simulation results show the effectiveness of the proposed scheme.

Original languageEnglish
Title of host publicationIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
PublisherIEEE Computer Society
ISBN (Electronic)9798350331820
DOIs
StatePublished - 2023
Event49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 - Singapore, Singapore
Duration: 16 Oct 202319 Oct 2023

Publication series

NameIECON Proceedings (Industrial Electronics Conference)
ISSN (Print)2162-4704
ISSN (Electronic)2577-1647

Conference

Conference49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Country/TerritorySingapore
CitySingapore
Period16/10/2319/10/23

Keywords

  • Actor-Critic Learning
  • Air-Floating Robot
  • Fixed-Time Control
  • Model Uncertainties

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