Attitude Constrained Control on SO(3): An Explicit Reference Governor Approach

Satoshi Nakano, Tam W. Nguyen, Emanuele Garone, Tatsuya Ibuki, Mitsuji Sampei

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

4 Scopus citations

Abstract

This paper focuses on the attitude constrained control of a rigid body in three dimensions, and proposes the Explicit Reference Governor (ERG) as a solution to handle constraints on SO (3). Two types of constraints are considered: (i) input torque constraints, and (ii) geometric conic pointing constraints. The objective of this paper is to design a control law that is able to steer the attitude of the rigid body to the desired attitude reference while enforcing constraints satisfaction at all times. To do so, the first step is to design a controller that makes the desired attitude asymptotically stable when constraints (i) and (ii) are neglected. Then, the proposed control scheme is augmented with a suitably designed ERG to add constraint-handling capabilities to the scheme. All the proposed solutions are defined in terms of elements on SO (3) and do not make use of any parameterizations such as e.g., quaternions and Euler angles. Finally, numerical simulations are carried out to show the effectiveness of the proposed control scheme.

Original languageEnglish
Title of host publication2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1833-1838
Number of pages6
ISBN (Electronic)9781538613955
DOIs
StatePublished - 2018/07/02
Event57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States
Duration: 2018/12/172018/12/19

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2018-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference57th IEEE Conference on Decision and Control, CDC 2018
Country/TerritoryUnited States
CityMiami
Period2018/12/172018/12/19

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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