Litcius/Paper detail

Semiglobal Consensus of a Class of Heterogeneous Multi-Agent Systems With Saturation

Kexin Liu, Haibo Gu, Wei Wang, Jinhu Lü

2020IEEE Transactions on Neural Networks and Learning Systems30 citationsDOI

Abstract

This article addresses the leader-following consensus of a class of multi-agent systems (MASs) subjected to saturation. Unlike previous literature, the followers are with heterogeneous dynamics. To solve this problem, we employ the low-gain feedback technique and the parameterized algebraic Riccati equations to design the controllers. For the fixed and switching network topologies, sufficient conditions are put in place to guarantee the semiglobal stability of the consensus error system. Numerical results are also provided to validate the effectiveness of the control design.

Topics & Concepts

Parameterized complexityControl theory (sociology)Computer scienceClass (philosophy)Multi-agent systemConsensusSaturation (graph theory)Network topologyAlgebraic Riccati equationAlgebraic numberMathematical optimizationStability (learning theory)MathematicsControl (management)Riccati equationAlgorithmArtificial intelligenceComputer networkMachine learningMathematical analysisDifferential equationCombinatoricsDistributed Control Multi-Agent SystemsNeural Networks Stability and SynchronizationMathematical and Theoretical Epidemiology and Ecology Models