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An Improved Stability Theorem for Nonlinear Systems on Time Scales With Application to Multi-Agent Systems

Xiaodong Lü, Haitao Li

2020IEEE Transactions on Circuits & Systems II Express Briefs40 citationsDOI

Abstract

In this brief, stability analysis of nonlinear systems on time scales is further investigated. The traditional stability theorems require the time-scale derivative of related Lyapunov function to be negative, which are conservative. Based on the induction principle on time scales, an improved stability theorem is proposed in this brief by introducing the time-scale type uniformly asymptotically stable function. It is shown that this improved stability theorem weakens the negativity restriction on the time-scale derivative of related Lyapunov function. Then, this improved stability theorem is applied to solve consensus problem of multi-agent systems on time scales. A numerical example is given to illustrate the effectiveness of the theoretic results.

Topics & Concepts

Nonlinear systemLyapunov functionStability (learning theory)MathematicsStability theoryApplied mathematicsLyapunov stabilityScale (ratio)Control theory (sociology)Function (biology)Time derivativeSmall-gain theoremMathematical analysisComputer scienceControl (management)PhysicsMachine learningQuantum mechanicsBiologyArtificial intelligenceEvolutionary biologyDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationMathematical and Theoretical Epidemiology and Ecology Models