Distributed Optimization Approach for Solving Continuous-Time Lyapunov Equations with Exponential Rate of Convergence

Xianlin Zeng; Jie Chen; Jian Sun; Yiguang Hong

doi:10.1109/TSMC.2020.3034229

Distributed Optimization Approach for Solving Continuous-Time Lyapunov Equations with Exponential Rate of Convergence

Xianlin Zeng^*
, Jie Chen
, Jian Sun
, Yiguang Hong

^*Corresponding author for this work

School of Automation

Beijing Institute of Technology
Tongji University
CAS - Academy of Mathematics and System Sciences

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

16 Citations (Scopus)

Abstract

This article establishes an approach, based on distributed optimization, for solving continuous-time Lyapunov equations (CTLE) over multiagent networks. Each agent in the network knows partial information of the CTLE and has a dynamical system to estimate exact or least-squares solutions. The aim of agents is to find a solution to CTLE by sharing information with connected agents over a network. This article develops distributed algorithms with an exponential rate of convergence for CTLE via the convex optimization design. Finally, this article presents numerical simulations to show the efficacy of the main results.

Original language	English
Pages (from-to)	1684-1691
Number of pages	8
Journal	IEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume	52
Issue number	3
DOIs	https://doi.org/10.1109/TSMC.2020.3034229
Publication status	Published - 1 Mar 2022

Keywords

Continuous-time Lyapunov equation (CTLE)
distributed optimization
exponential convergence rate

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10.1109/TSMC.2020.3034229

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title = "Distributed Optimization Approach for Solving Continuous-Time Lyapunov Equations with Exponential Rate of Convergence",

abstract = "This article establishes an approach, based on distributed optimization, for solving continuous-time Lyapunov equations (CTLE) over multiagent networks. Each agent in the network knows partial information of the CTLE and has a dynamical system to estimate exact or least-squares solutions. The aim of agents is to find a solution to CTLE by sharing information with connected agents over a network. This article develops distributed algorithms with an exponential rate of convergence for CTLE via the convex optimization design. Finally, this article presents numerical simulations to show the efficacy of the main results.",

keywords = "Continuous-time Lyapunov equation (CTLE), distributed optimization, exponential convergence rate",

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

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AU - Zeng, Xianlin

AU - Chen, Jie

AU - Sun, Jian

AU - Hong, Yiguang

PY - 2022/3/1

Y1 - 2022/3/1

N2 - This article establishes an approach, based on distributed optimization, for solving continuous-time Lyapunov equations (CTLE) over multiagent networks. Each agent in the network knows partial information of the CTLE and has a dynamical system to estimate exact or least-squares solutions. The aim of agents is to find a solution to CTLE by sharing information with connected agents over a network. This article develops distributed algorithms with an exponential rate of convergence for CTLE via the convex optimization design. Finally, this article presents numerical simulations to show the efficacy of the main results.

AB - This article establishes an approach, based on distributed optimization, for solving continuous-time Lyapunov equations (CTLE) over multiagent networks. Each agent in the network knows partial information of the CTLE and has a dynamical system to estimate exact or least-squares solutions. The aim of agents is to find a solution to CTLE by sharing information with connected agents over a network. This article develops distributed algorithms with an exponential rate of convergence for CTLE via the convex optimization design. Finally, this article presents numerical simulations to show the efficacy of the main results.

KW - Continuous-time Lyapunov equation (CTLE)

KW - distributed optimization

KW - exponential convergence rate

UR - https://www.scopus.com/pages/publications/85096868847

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DO - 10.1109/TSMC.2020.3034229

M3 - Article

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EP - 1691

JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems

JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems

IS - 3

ER -

Distributed Optimization Approach for Solving Continuous-Time Lyapunov Equations with Exponential Rate of Convergence

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Keywords

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