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Singular-Perturbation-based Intelligent Midcourse Guidance for Air-To-Air Missiles Equipped with Dual-Pulse Motor

  • Xiaopeng Gong*
  • , Wanchun Chen
  • , Zhongyuan Chen*
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents an intelligent midcourse guidance law applicable to a long-range air-To-Air missile equipped with a dual-pulse motor. Based on the traditional singular perturbation approach, deep reinforcement learning is introduced to generate secondary ignition commands and acceleration corrections, which enhance the performance of the guidance law at long guidance loop sampling periods and when parameters are not tuned. The approach of singular perturbation midcourse guidance is first reviewed, and then only one neural network is employed to perform the tasks of ignition and correction sequentially to save storage and computational resources. The simulation results show that the proposed method can be applied to attack long-range targets in beyond visual range air-To-Air engagement.

Original languageEnglish
Title of host publication2023 14th International Conference on Mechanical and Aerospace Engineering, ICMAE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages419-424
Number of pages6
ISBN (Electronic)9798350340327
DOIs
StatePublished - 2023
Event14th International Conference on Mechanical and Aerospace Engineering, ICMAE 2023 - Porto, Portugal
Duration: 18 Jul 2023 → 21 Jul 2023

Publication series

Name2023 14th International Conference on Mechanical and Aerospace Engineering, ICMAE 2023

Conference

Conference14th International Conference on Mechanical and Aerospace Engineering, ICMAE 2023
Country/TerritoryPortugal
CityPorto
Period18/07/23 → 21/07/23

Keywords

  • air-To-Air engagement
  • deep reinforcement learning
  • dual-pulse motor
  • midcourse guidance
  • singular perturbation

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