Robust control under worst‐case uncertainty for unknown nonlinear systems using modified reinforcement learning

DOI10.1002/RNC.4911zbMath1465.93052OpenAlexW3007973969MaRDI QIDQ4990480

Adolfo Perrusquía, Wen Yu

Publication date: 28 May 2021

Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rnc.4911

zbMATH Keywords

overestimation\(k\)-nearest neighborsworst-case uncertaintyrobust rewarddouble estimatorstate-action space

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) Nonlinear systems in control theory (93C10) Control/observation systems with incomplete information (93C41)

Related Items (6)

Stable robot manipulator parameter identification: a closed-loop input error approach ⋮ Robust state/output feedback linearization of direct drive robot manipulators: a controllability and observability analysis ⋮ Nonlinear control using human behavior learning ⋮ Deep Q‐learning: A robust control approach ⋮ Solution of the linear quadratic regulator problem of black box linear systems using reinforcement learning ⋮ Continuous-time reinforcement learning for robust control under worst-case uncertainty

This page was built for publication: Robust control under worst‐case uncertainty for unknown nonlinear systems using modified reinforcement learning