Iterative learning control approach for a kind of heterogeneous multi-agent systems with distributed initial state learning

DOI10.1016/j.amc.2015.06.035zbMath1410.93012OpenAlexW1124303512MaRDI QIDQ1664295

Junmin Li, Jinsha Li

Publication date: 24 August 2018

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2015.06.035

zbMATH Keywords

iterative learning controlheterogeneous systemsmulti-agent systemsconsensus algorithmdistributed initial state learning controller

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) System identification (93B30) Decentralized systems (93A14) Distributed systems (68M14) Agent technology and artificial intelligence (68T42)

Related Items (11)

Robust iterative learning control design for linear systems with time-varying delays and packet dropouts ⋮ The effect of initial state error for nonlinear systems with delay via iterative learning control ⋮ Consensus control for multi-agent systems with distributed parameter models via iterative learning algorithm ⋮ Consensus control for multi-agent systems with quasi-one-sided Lipschitz nonlinear dynamics via iterative learning algorithm ⋮ Leader-following consensus for second-order nonlinear multiagent systems with input saturation via distributed adaptive neural network iterative learning control ⋮ Consensus tracking via quantized iterative learning control for singular nonlinear multi-agent systems with state time-delay and initial state error ⋮ Consensus tracking problem for linear fractional multi-agent systems with initial state error ⋮ Output information based fault-tolerant iterative learning control for dual-rate sampling process with disturbances and output delay ⋮ Distributed adaptive fixed-time consensus tracking for second-order multi-agent systems using modified terminal sliding mode ⋮ Event-triggered learning consensus of networked heterogeneous nonlinear agents with switching topologies ⋮ Hybrid online learning control in networked multiagent systems: A survey

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