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Two-degree-of-freedom control combining machine learning and extremum seeking for fast scanning quantum dot microscopy.

, , , , and . ACC, page 4360-4366. IEEE, (2018)

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Exact Multiple-Step Predictions in Gaussian Process-based Model Predictive Control: Observations, Possibilities, and Challenges., , and . ACC, page 2829-2836. IEEE, (2022)Control of Scanning Quantum Dot Microscopy., , , , , , and . CoRR, (2021)Online Gaussian Process learning-based Model Predictive Control with Stability Guarantees., , and . CoRR, (2019)Optimal Operation and Control of Towing Kites using Online and Offline Gaussian Process Learning Supported Model Predictive Control., , and . ACC, page 2637-2643. IEEE, (2022)Path Following or Tracking Model Predictive Control for Towing Kites - A Question of Formulation or Learning?, , and . CCTA, page 459-465. IEEE, (2023)Fusing Online Gaussian Process-Based Learning and Control for Scanning Quantum Dot Microscopy., , , , and . CDC, page 5525-5531. IEEE, (2020)Two-degree-of-freedom control combining machine learning and extremum seeking for fast scanning quantum dot microscopy., , , , and . ACC, page 4360-4366. IEEE, (2018)Manipulation on a molecular level: towards controlled molecular 3D printing., , , and . ACC, page 3094. IEEE, (2016)Control on a molecular scale: A perspective., , , , , , , , , and . ACC, page 3069-3082. IEEE, (2016)