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

9 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

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10.1109/TCYB.2020.3000791

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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

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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",

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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.

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KW - distributed optimization

KW - matrix inequality

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Distributed Optimization Design for Computation of Algebraic Riccati Inequalities

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Keywords

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