Litcius/Paper detail

On Necessary and Sufficient Conditions for Exponential Consensus in Dynamic Networks via Uniform Complete Observability Theory

Qichao Ma, Jiahu Qin, Xinghuo Yu, Long Wang

2020IEEE Transactions on Automatic Control26 citationsDOI

Abstract

In this article, we deal with the consensus problem of multiple partial-state coupled linear systems, which are neutrally stable. These systems communicate over dynamic undirected networks, which change continuously and can be disconnected at any time. We develop an analysis framework from uniform complete observability theory to work out <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">the necessary and sufficient conditions</i> for exponential consensus. It turns out that, with a suitably designed feedback matrix, exponential consensus can be realized globally and uniformly <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">if and only if</i> a jointly <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(\delta,T)$</tex-math></inline-formula> -connected condition and an observability condition relying only on system and input matrices are satisfied. A lower bound of the convergence rate is also provided. We figure out the proof by applying matrix analysis and linear functional analysis. A simulation example is presented to illustrate our theoretical findings.

Topics & Concepts

ObservabilityExponential functionMathematicsComputer scienceMatrix (chemical analysis)State (computer science)Discrete mathematicsMatrix exponentialApplied mathematicsAlgorithmCombinatoricsTheoretical computer scienceMathematical analysisMaterials scienceDifferential equationComposite materialDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationAdvanced Memory and Neural Computing