Analytical solutions of the controller matching problem based on inverse lqr for spacecraft relative dynamics

Dae Eun Kang, Hancheol Cho, Sang Young Park

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper studies analytical solutions of the controller matching problem based on inverse LQR which works for any prediction horizon. The solutions are applied to model predictive control (MPC) to make its performance the same as a preassigned linear state-feedback controller when constraints are not active. The problem is solved for linearized relative dynamics of spacecraft described by the Clohessy-Wiltshire equations and the solutions comprise the weighting matrices associated with the MPC optimization problem. The designed MPC controller will be useful in the application of spacecraft rendezvous and docking as it behaves as the predesigned linear controller when constraints are inactive, while satisfying the constraints in an optimal manner when they are active. The solutions are separately derived for each of the out-of-plane and in-plane cases. Numerical simulations are carried out to demonstrate the effectiveness of the analytical solutions proposed herein.

Original languageEnglish
Title of host publicationAIAA Scitech 2021 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
Pages1-17
Number of pages17
ISBN (Print)9781624106095
Publication statusPublished - 2021
EventAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021 - Virtual, Online
Duration: 2021 Jan 112021 Jan 15

Publication series

NameAIAA Scitech 2021 Forum

Conference

ConferenceAIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021
CityVirtual, Online
Period21/1/1121/1/15

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2019R1F1A1043859).

Publisher Copyright:
© 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering

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