Distributed Optimization Design for Computation of Algebraic Riccati Inequalities

Xianlin Zeng*, Jie Chen, Yiguang Hong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

This article proposes a distributed optimization design to compute continuous-time algebraic Riccati inequalities (ARIs), where the information of matrices is distributed among agents. We propose a design procedure to tackle the nonlinearity, the inequality, and the coupled information structure of ARI; then, we design a distributed algorithm based on an optimization approach and analyze its convergence properties. The proposed algorithm is able to verify whether ARI is feasible in a distributed way and converges to a solution if ARI is feasible for any initial condition.

Original languageEnglish
Pages (from-to)1924-1935
Number of pages12
JournalIEEE Transactions on Cybernetics
Volume52
Issue number3
DOIs
Publication statusPublished - 1 Mar 2022

Keywords

  • Distributed algorithm
  • distributed optimization
  • matrix inequality

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