Robust Output Regulation and Reinforcement Learning-Based Output Tracking Design for Unknown Linear Discrete-Time Systems

DOI10.1109/TAC.2022.3172590zbMath1529.93050arXiv2101.08706OpenAlexW3121634745MaRDI QIDQ6053282

Xie, Lihua, Ci Chen, Unnamed Author, Kan Xie, Sheng-Li Xie

Publication date: 26 September 2023

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2101.08706

zbMATH Keywords

output trackingrobust output regulationadaptive optimal controlreinforcement learning (RL)

Mathematics Subject Classification ID

Adaptive control/observation systems (93C40) Discrete-time control/observation systems (93C55) Observers (93B53)

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Adaptive Optimal Control of Linear Discrete-Time Networked Control Systems with Two-Channel Stochastic Dropouts ⋮ Data-driven optimal output regulation for unknown linear discrete-time systems based on parameterization approach ⋮ Distributed output data-driven optimal robust synchronization of heterogeneous multi-agent systems ⋮ Specified convergence rate guaranteed output tracking of discrete-time systems via reinforcement learning ⋮ Control policy learning design for vehicle urban positioning via BeiDou navigation ⋮ Incremental reinforcement learning and optimal output regulation under unmeasurable disturbances

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