A Modified Adaptive-gain Super-twisting Sliding Mode Guidance with Impact Angle Constraint *

  • Xuman An
  • , Xiaofei Yang
  • , Yunjie Wu
  • , Bohao Li
  • , Fei Ma

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

Abstract

In this study, a modified adaptive-gain super-twisting sliding mode guidance law with finite time convergence is proposed to intercept targets with impact angle constraint. The proposed guidance law introduces a linear term and an inner negative feedback so as to restrain the overshoot and enhance the performance of faster convergence. Furthermore, the adaptive-gain schedule can attenuate the chattering in the presence of the perturbations with the unknown boundaries. The finite time stability of the guidance law is analyzed. Simulation results show that the proposed guidance law is able to achieve more satisfactory interception.

Original languageEnglish
Title of host publication2022 IEEE 17th International Conference on Control and Automation, ICCA 2022
PublisherIEEE Computer Society
Pages654-659
Number of pages6
ISBN (Electronic)9781665495721
DOIs
StatePublished - 2022
Event17th IEEE International Conference on Control and Automation, ICCA 2022 - Naples, Italy
Duration: 27 Jun 202230 Jun 2022

Publication series

NameIEEE International Conference on Control and Automation, ICCA
Volume2022-June
ISSN (Print)1948-3449
ISSN (Electronic)1948-3457

Conference

Conference17th IEEE International Conference on Control and Automation, ICCA 2022
Country/TerritoryItaly
CityNaples
Period27/06/2230/06/22

Keywords

  • Super-twisting
  • adaptive-gain
  • impact angle constraint
  • inner feedback
  • linear term

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