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Analysis of ${H}_{\infty }$ Performance for Multiagent Networks

Jiamin Wang, Jian Liu, Yuanshi Zheng, Jianxiang Xi

2023IEEE Transactions on Automatic Control27 citationsDOI

Abstract

In this paper, we analyze the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_{\infty }$</tex-math></inline-formula> performance of the first-order continuous-time multi-agent consensus network and that of the corresponding sampled-data network in the presence of external disturbances. Firstly, we build the quantitative relation between the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_{\infty }$</tex-math></inline-formula> performance and the eigenvalues of directed graph Laplacian for the continuous-time multi-agent network. Secondly, we establish the analytic expression of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_{\infty }$</tex-math></inline-formula> performance for the sampled-data multi-agent network, which depends not only the eigenvalues of Laplacian matrix but also the sampling period. It is proved that there exists a unique optimal sampling period such that the sampled-data multi-agent network obtains the optimal <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_{\infty }$</tex-math></inline-formula> performance. Furthermore, we show that the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${H}_{\infty }$</tex-math></inline-formula> performance of the sampled-data multi-agent network is not better than that of the original continuous-time multi-agent network. Finally, numerical tests are given on several well-known graphs.

Topics & Concepts

NotationEigenvalues and eigenvectorsLaplacian matrixMathematicsGraphNetwork topologyCombinatoricsAlgorithmDiscrete mathematicsAlgebra over a fieldComputer sciencePure mathematicsArithmeticOperating systemPhysicsQuantum mechanicsDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationAdvanced Memory and Neural Computing
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