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The code accompanies the publication "An Uncertainty-based Control Lyapunov Approach for Control-affine Systems Modeled by Gaussian Process" by Jonas Umlauft, Lukas Pöhler, Sandra Hirche published in IEEE Control Systems Letters (L-CSS) in 2018

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The provided Matlab code accompanies the following publication:

@ARTICLE{8368325, author={J. Umlauft and L. Pöhler and S. Hirche}, journal={IEEE Control Systems Letters}, title={An Uncertainty-Based Control Lyapunov Approach for Control-Affine Systems Modeled by Gaussian Process}, year={2018}, volume={2}, number={3}, pages={483-488}, keywords={asymptotic stability;control system synthesis;dynamic programming;Gaussian processes;Lyapunov methods;nonlinear control systems;probability;uncertain systems;control Lyapunov approach;stabilizing control law;Gaussian process model;nonlinear system;uncertainty model;asymptotically stability;actuated control affine system;probability system;fidelity estimation;power constraint;dynamic programming;Kernel;Data models;Unified modeling language;Training data;Gaussian processes;Lyapunov methods;Control systems;Lyapunov methods;machine learning;uncertain systems;robust control;nonlinear systems identification}, doi={10.1109/LCSYS.2018.2841961}, ISSN={2475-1456}, month={July}, }

Please acknowledge the authors in any academic publication that have made use of this code or parts of it by referencing to the paper.

The most recent version is available at: https://gitlab.lrz.de/ga68car/OptUCLF4GP.git

Please send your feedbacks or questions to: jonas.umlauft_at_tum.de

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The code accompanies the publication "An Uncertainty-based Control Lyapunov Approach for Control-affine Systems Modeled by Gaussian Process" by Jonas Umlauft, Lukas Pöhler, Sandra Hirche published in IEEE Control Systems Letters (L-CSS) in 2018

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