Optimal Tracking Guidance for Aeroassisted Spacecraft Reconnaissance Mission Based on Receding Horizon Control

Runqi Chai, Al Savvaris, Antonios Tsourdos, Senchun Chai*, Yuanqing Xia

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)

Abstract

This paper focuses on the application of model predictive control (MPC) for the spacecraft trajectory tracking problems. The motivation of the use of MPC, also known as receding horizon control, relies on its ability in dealing with control, state, and path constraints that naturally arise in practical trajectory planning problems. Two different MPC schemes are constructed to solve the reconnaissance trajectory tracking problem. Since the MPC solves the online optimal control problems at each sampling instant, the computational cost associated with it can be high. In order to decrease the computational demand due to the optimization process, a newly proposed two-nested gradient method is used and embedded in the two MPC schemes. Simulation results are provided to illustrate the effectiveness and feasibility of the two MPC tracking algorithms combined with the improved optimization technique.

Original languageEnglish
Article number8269278
Pages (from-to)1575-1588
Number of pages14
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume54
Issue number4
DOIs
Publication statusPublished - Aug 2018

Keywords

  • Model Predictive Control
  • optimal control
  • receding horizon control
  • spacecraft trajectory tracking
  • two-nested gradient method

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