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Shrinking Horizon MPC Strategy for Impact Time and Angle Guidance

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

Abstract

In this paper, a new model predictive control (MPC) strategy is proposed for the impact-time-and-angle guidance problem subject to input limits. The nonlinear dynamic model of the guidance system is linearized by first-order Taylor-series expansions, resulting in an optimization problem that can be effectively solved via convex programming solvers. The prediction and control horizons of the MPC strategy are adaptively shrinking to cover the whole mission duration. Therefore, the terminal impact time and angle constraints can be integrated into the optimization procedure even during the early guidance phase. The robustness, control-effort optimality, and computational simplicity of the new MPC strategy are demonstrated via numerical simulations.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Pages3667-3672
Number of pages6
ISBN (Electronic)9789881563804
DOIs
StatePublished - 26 Jul 2021
Externally publishedYes
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
Volume2021-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference40th Chinese Control Conference, CCC 2021
Country/TerritoryChina
CityShanghai
Period26/07/2128/07/21

Keywords

  • Impact-Time-and-Angle Guidance
  • Model Predictive Control
  • Shrinking Horizons

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