Adaptive iterative learning protocol design for nonlinear multi-agent systems with unknown control direction

DOI10.1016/j.jfranklin.2018.04.012zbMath1390.93445OpenAlexW2798236320MaRDI QIDQ1644284

Junmin Li, Jinsha Li, San-Yang Liu

Publication date: 21 June 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.2018.04.012

zbMATH Keywords

uncertain nonlinear multi-agent systemsNussbaum gainadaptive iterative learning control protocol designunknown gain signs

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Adaptive control/observation systems (93C40) Decentralized systems (93A14) Agent technology and artificial intelligence (68T42)

Related Items (9)

Globally repetitive learning consensus control of unknown nonlinear multi-agent systems with uncertain time-varying parameters ⋮ Performance index based observer-type iterative learning control for consensus tracking of uncertain nonlinear fractional-order multiagent systems ⋮ Cooperative iterative learning for uncertain nonlinear agents in leaderless switching networks ⋮ Global consensus of second‐order unknown multi‐agent systems: A distributed fuzzy iterative learning scheme ⋮ Global iterative learning control based on fuzzy systems for nonlinear multi-agent systems with unknown dynamics ⋮ Consensus tracking via quantized iterative learning control for singular nonlinear multi-agent systems with state time-delay and initial state error ⋮ 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 learning consensus control of high‐order multiagent systems with imprecise communication topology structure ⋮ Consensus control of leader-following nonlinear multi-agent systems with distributed adaptive iterative learning control

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