Distributed Optimization Design of Iterative Refinement Technique for Algebraic Riccati Equations

Xianlin Zeng*, Jie Chen, Yiguang Hong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

This article focuses on the problem of a distributed computation of continuous-time algebraic Riccati equations (CARE), where information of matrices is split and known by multiple agents. This article proposes a distributed optimization design of the iterative refinement technique (IRM), a well-established centralized method for CARE. By assuming that each agent only knows partial information of CARE, we reformulate IRM for CARE as three classes of distributed optimization subproblems with different formulations and constraints. Then, we propose distributed algorithms for obtained distributed optimization subproblems and prove convergence properties of proposed algorithms. Numerical results show the efficacy of the proposed distributed IRM.

Original languageEnglish
Pages (from-to)2833-2847
Number of pages15
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume52
Issue number5
DOIs
Publication statusPublished - 1 May 2022

Keywords

  • Continuous-time algebraic Riccati equation (CARE)
  • distributed algorithm
  • distributed optimization
  • iterative refinement method

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