Distributed adaptive repetitive consensus control framework for uncertain nonlinear leader-follower multi-agent systems

DOI10.1016/j.jfranklin.2015.09.008zbMath1395.93016OpenAlexW2118207835MaRDI QIDQ1660757

Jinsha Li, Daniel W. C. Ho, Junmin Li

Publication date: 16 August 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2015.09.008

zbMATH Keywords

distributed adaptive repetitive consensus controluncertain nonlinear leader-follower multi-agent systems

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Nonlinear systems in control theory (93C10) Control/observation systems with incomplete information (93C41) Design techniques (robust design, computer-aided design, etc.) (93B51) Adaptive control/observation systems (93C40) Hierarchical systems (93A13) Decentralized systems (93A14) Control/observation systems governed by ordinary differential equations (93C15) Agent technology and artificial intelligence (68T42)

Related Items (14)

Globally repetitive learning consensus control of unknown nonlinear multi-agent systems with uncertain time-varying parameters ⋮ Fully distributed neural control of periodically time-varying parameterized stochastic nonlinear multi-agent systems with hybrid-order dynamics ⋮ Task-space coordinated tracking of multiple heterogeneous manipulators via controller-estimator approaches ⋮ Adaptive finite-time consensus of a class of disturbed multi-agent systems ⋮ Distributed adaptive output-feedback tracking control of non-affine multi-agent systems with prescribed performance ⋮ Globally fuzzy leader-follower consensus of mixed-order nonlinear multi-agent systems with partially unknown direction control ⋮ Adaptive neural tracking control for stochastic nonlinear multi-agent periodic time-varying systems ⋮ Finite-time and fixed-time bipartite consensus of multi-agent systems under a unified discontinuous control protocol ⋮ Distributed sensor fault diagnosis for a formation of multi-vehicle systems ⋮ Distributed consensus control of periodically time-varying multi-agent systems using neural networks and Fourier series expansion ⋮ Reliable consensus control for semi-Markov jump multi-agent systems: a leader-following strategy ⋮ Mixed time/event-triggered distributed predictive control over wired-wireless networks ⋮ New distributed adaptive protocols for uncertain nonlinear leader-follower multi-agent systems via a repetitive learning control approach ⋮ T–S fuzzy model-based adaptive repetitive consensus control for multi-agent systems with imprecise communication topology structure

Cites Work

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