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Distributed solver for linear matrix inequalities:an optimization perspective

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In this paper,we develop a distributed solver for a group of strict(non-strict)linear matrix inequalities over a multi-agent network,where each agent only knows one inequality,and all agents co-operate to reach a consensus solution in the inter-section of all the feasible regions.The formulation is transformed into a distributed optimization problem by introducing slack variables and consensus constraints.Then,by the primal-dual methods,a distributed algorithm is proposed with the help of projection operators and derivative feedback.Finally,the convergence of the algorithm is analyzed,followed by illustrative simulations.

Distributed computationDistributed optimizationLinear matrix inequalitiesPrimal-dual method

Weijian Li、Wen Deng、Xianlin Zeng、Yiguang Hong

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Department of Automation,University of Science and Technology of China,Hefei 230027,Anhui,China

Key Lab of Systems and Control,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China

Key Laboratory of Intelligent Control and Decision of Complex Systems,School of Automation,Beijing Institute of Technology,Beijing 100081,China

Department of Control Science and Engineering,Tongji University,Shanghai 201804,China

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Shanghai Municipal Science and Technology Major ProjectNational Natural Science Foundation of ChinaNational Natural Science Foundation of China

2021SHZDZX01006173301862073035

2021

控制理论与技术(英文版)
华南理工大学

控制理论与技术(英文版)

CSCDEI
影响因子：0.307
ISSN：2095-6983
年,卷(期)：2021.19(4)
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