A Fused Gaussian Process Modeling and Model Predictive Control Framework for Real-Time Path Adaptation of an Airborne Wind Energy System

Siddiqui, Ayaz; Borek, John; Vermillion, Chris

doi:10.1109/tcst.2022.3178038

A Fused Gaussian Process Modeling and Model Predictive Control Framework for Real-Time Path Adaptation of an Airborne Wind Energy System

Journal Article · 01 January 2023 · IEEE Transactions on Control Systems Technology

DOI:https://doi.org/10.1109/tcst.2022.3178038· OSTI ID:2418644

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Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA; OSTI
Department of Mechanical Engineering, University of North Carolina at Charlotte, Charlotte, NC, USA
Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA

Not provided.

Research Organization:: North Carolina State University, Raleigh, NC (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

DOE Contract Number:: EE0008635

OSTI ID:: 2418644

Journal Information:: IEEE Transactions on Control Systems Technology, Journal Name: IEEE Transactions on Control Systems Technology Journal Issue: 1 Vol. 31; ISSN 1063-6536

Publisher:: IEEE

Country of Publication:: United States

Language:: English

References (17)

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Spatiotemporal Optimization Through Gaussian Process-Based Model Predictive Control: A Case Study in Airborne Wind Energy Bin-Karim, Shamir; Bafandeh, Alireza; Baheri, Ali IEEE Transactions on Control Systems Technology, Vol. 27, Issue 2 https://doi.org/10.1109/TCST.2017.2779428	journal	March 2019
Optimal Crosswind Towing and Power Generation with Tethered Kites Williams, Paul; Lansdorp, Bas; Ockesl, Wubbo Journal of Guidance, Control, and Dynamics, Vol. 31, Issue 1 https://doi.org/10.2514/1.30089	journal	January 2008
Real-Time Optimization and Adaptation of the Crosswind Flight of Tethered Wings for Airborne Wind Energy Zgraggen, Aldo U.; Fagiano, Lorenzo; Morari, Manfred IEEE Transactions on Control Systems Technology, Vol. 23, Issue 2 https://doi.org/10.1109/TCST.2014.2332537	journal	March 2015
A Gaussian Process-Based Receding Horizon Adaptive Control Strategy for Energy-Efficient Exploration of Spatiotemporally Varying Environments, with Application to Airborne Wind Energy Systems Siddiqui, Ayaz; Haydon, Ben; Vermillion, Chris 2021 American Control Conference (ACC) https://doi.org/10.23919/ACC50511.2021.9482867	conference	May 2021
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On Wind Speed Sensor Configurations and Altitude Control in Airborne Wind Energy Systems Dunn, Laurel N.; Vermillion, Christopher; Chow, Fotini K. 2019 American Control Conference (ACC) https://doi.org/10.23919/ACC.2019.8814364	conference	July 2019
Optimal Exploration and Charging for an Autonomous Underwater Vehicle with Energy-Harvesting Kite Reed, James; Daniels, Joshua; Siddiqui, Ayaz 2020 American Control Conference (ACC) https://doi.org/10.23919/ACC45564.2020.9147746	conference	July 2020
Iterative Learning-Based Path Optimization for Repetitive Path Planning, With Application to 3-D Crosswind Flight of Airborne Wind Energy Systems Cobb, Mitchell K.; Barton, Kira; Fathy, Hosam IEEE Transactions on Control Systems Technology, Vol. 28, Issue 4 https://doi.org/10.1109/TCST.2019.2912345	journal	July 2020
Machine learning meets Kalman Filtering Carron, Andrea; Todescato, Marco; Carli, Ruggero 2016 IEEE 55th Conference on Decision and Control (CDC) https://doi.org/10.1109/CDC.2016.7798968	conference	December 2016
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Altitude optimization of Airborne Wind Energy systems: A Bayesian Optimization approach Baheri, Ali; Vermillion, Christopher 2017 American Control Conference (ACC) https://doi.org/10.23919/ACC.2017.7963143	conference	May 2017
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