Range guidance for subsonic unpowered gliding vehicle using integral action-based sliding mode control

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Range enhancement for a Subsonic Unpowered Gliding Vehicle (SUGV) is an interesting and challenging problem because it depends only on mechanically stored energy. In this study, the inverted Y-tail joint stand-off weapon is selected as the SUGV. To increase the range, a range guidance scheme has been developed which depends on the dispersion points and the angle of attack. To overcome saturation effect in range guidance command and nonsmooth range guidance command that cause a terminal error in range, an Integral Action-based Sliding Mode Control (IA SMC) methodology is proposed. The stability analysis of the IA SMC is also established by the quadratic Lyapunov function. To deal with the chattering problem in SMC and enhance the velocity of reaching phase, a tan-1-based strong exponential reaching law is also employed. When compared with the PID-based sliding surface dependent SMC (PID SMC) to achieve a range of 125 km, MATLAB simulation results show that IA SMC generates smooth guidance command and reduces the saturation effects and terminal error in the range. Furthermore, the quantitative analysis shows that the effectiveness of IA SMC is better than that of PID SMC.

Original languageEnglish
Pages (from-to)785-795
Number of pages11
JournalInternational Journal of Dynamics and Control
Volume12
Issue number3
DOIs
StatePublished - Mar 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.

Keywords

  • Integral action
  • PID sliding surface
  • Range guidance law
  • Reaching law
  • Sliding mode control
  • Subsonic
  • Unpowered gliding vehicle

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Modeling and Simulation
  • Mechanical Engineering
  • Control and Optimization
  • Electrical and Electronic Engineering

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