Optimal Operation and Control of Towing Kites using Online and Offline Gaussian Process Learning Supported Model Predictive Control-Reference-Cited by-同舟云学术

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Optimal Operation and Control of Towing Kites using Online and Offline Gaussian Process Learning Supported Model Predictive Control

Published:2022-06-08 Issue: Volume: Page:
ISSN:
Container-title:2022 American Control Conference (ACC)
language:
Short-container-title:

Author:

Eckel Christina¹,Maiworm Michael²,Findeisen Rolf³

Affiliation:

1. Hamburg University of Technology,Institute of Electrical Power and Energy Technology,Hamburg,Germany

2. Otto-von-Guericke-University,Laboratory for Systems Theory and Automatic Control,Magdeburg,Germany

3. Technische Universität Darmstadt,Laboratory for Control of Cyber-physical Systems and Mechatronics,Darmstadt,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9866948/9867142/09867371.pdf?arnumber=9867371

Reference36 articles.

1. Fault Tolerant Control Using Gaussian Processes and Model Predictive Control

2. Gaussian process approach for modelling of nonlinear systems

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

4. Predictive control with Gaussian process models

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unmatched Uncertainty Mitigation Through Neural Network Supported Model Predictive Control;2023 62nd IEEE Conference on Decision and Control (CDC);2023-12-13

2. Path Following or Tracking Model Predictive Control for Towing Kites – A Question of Formulation or Learning?;2023 IEEE Conference on Control Technology and Applications (CCTA);2023-08-16

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