Distributed Optimization Design for Computation of Algebraic Riccati Inequalities

Xianlin Zeng; Jie Chen; Yiguang Hong

doi:10.1109/TCYB.2020.3000791

Distributed Optimization Design for Computation of Algebraic Riccati Inequalities

Xianlin Zeng^*, Jie Chen, Yiguang Hong

^*Corresponding author for this work

School of Automation

Research output: Contribution to journal › Article › peer-review

8 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 language	English
Pages (from-to)	1924-1935
Number of pages	12
Journal	IEEE Transactions on Cybernetics
Volume	52
Issue number	3
DOIs	https://doi.org/10.1109/TCYB.2020.3000791
Publication status	Published - 1 Mar 2022

Keywords

Distributed algorithm
distributed optimization
matrix inequality

Access to Document

10.1109/TCYB.2020.3000791

Cite this

Zeng, X., Chen, J., & Hong, Y. (2022). Distributed Optimization Design for Computation of Algebraic Riccati Inequalities. IEEE Transactions on Cybernetics, 52(3), 1924-1935. https://doi.org/10.1109/TCYB.2020.3000791

@article{d937f82b1ffa4729b05c1dd4b190a0f2,

title = "Distributed Optimization Design for Computation of Algebraic Riccati Inequalities",

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.",

keywords = "Distributed algorithm, distributed optimization, matrix inequality",

author = "Xianlin Zeng and Jie Chen and Yiguang Hong",

note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",

year = "2022",

month = mar,

day = "1",

doi = "10.1109/TCYB.2020.3000791",

language = "English",

volume = "52",

pages = "1924--1935",

journal = "IEEE Transactions on Cybernetics",

issn = "2168-2267",

publisher = "IEEE Advancing Technology for Humanity",

number = "3",

}

TY - JOUR

T1 - Distributed Optimization Design for Computation of Algebraic Riccati Inequalities

AU - Zeng, Xianlin

AU - Chen, Jie

AU - Hong, Yiguang

PY - 2022/3/1

Y1 - 2022/3/1

N2 - 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.

AB - 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.

KW - Distributed algorithm

KW - distributed optimization

KW - matrix inequality

UR - http://www.scopus.com/inward/record.url?scp=85126389771&partnerID=8YFLogxK

U2 - 10.1109/TCYB.2020.3000791

DO - 10.1109/TCYB.2020.3000791

M3 - Article

C2 - 32609618

AN - SCOPUS:85126389771

SN - 2168-2267

VL - 52

SP - 1924

EP - 1935

JO - IEEE Transactions on Cybernetics

JF - IEEE Transactions on Cybernetics

IS - 3

ER -

Distributed Optimization Design for Computation of Algebraic Riccati Inequalities

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this