Stable Gaussian process based tracking control of Euler-Lagrange systems

DOI10.1016/j.automatica.2019.01.023zbMath1415.93289arXiv1806.07190OpenAlexW2808816909MaRDI QIDQ1737856

Thomas Beckers, Sandra Hirche, Dana Kulić

Publication date: 24 April 2019

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1806.07190

zbMATH Keywords

stochastic controlrobotic manipulatorsnonparametric methodsstability of nonlinear systemsdata-based controladaptive systemsl

Mathematics Subject Classification ID

Feedback control (93B52) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Automated systems (robots, etc.) in control theory (93C85) Optimal stochastic control (93E20) Stochastic stability in control theory (93E15)

Related Items

Robust adaptive trajectory tracking for wheeled mobile robots based on Gaussian process regression, Noniterative tensor network‐based algorithm for Volterra system identification, Hierarchical optimization for task-space bipartite coordination of multiple uncertain Lagrange plants, Fault-tolerant practical tracking control for uncertain robotic system with general reference trajectory and output constraint, An LMI framework for contraction-based nonlinear control design by derivatives of Gaussian process regression, Safe trajectory tracking for underactuated vehicles with partially unknown dynamics, Learning-based symbolic abstractions for nonlinear control systems

Uses Software

• PRMLT

Cites Work

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