Output-feedback optimized consensus for directed graph multi-agent systems based on reinforcement learning and subsystem error derivatives

DOI10.1016/J.INS.2023.119577zbMath1526.93241OpenAlexW4386071013MaRDI QIDQ6074943

Jiuxiang Dong, Dongdong Li

Publication date: 19 October 2023

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2023.119577

zbMATH Keywords

neural networkreinforcement learningstate observeroptimized backstepping controloutput-feedback consensus

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Feedback control (93B52) Multi-agent systems (93A16) Consensus (93D50)

Related Items (2)

Distributed fault-tolerant consensus for one-sided Lipschitz multiagent systems based on error decomposition and jointly observable condition ⋮ Neural network based adaptive finite-time distributed estimation for an uncertain leader

Cites Work

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• Event-triggered adaptive consensus for fuzzy output-constrained multi-agent systems with observers
• Q-learning solution for optimal consensus control of discrete-time multiagent systems using reinforcement learning
• A novel adaptive dynamic programming based on tracking error for nonlinear discrete-time systems
• Event-triggered output feedback consensus tracking control for nonlinear multiagent systems with sensor failures
• Performance-constrained fault-tolerant DSC based on reinforcement learning for nonlinear systems with uncertain parameters

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