Open AccessSpatiotemporal Optimization Through Gaussian Process-Based Model Predictive Control: A Case Study in Airborne Wind Energy
Author(s) -
Shamir Bin-Karim,
Alireza Bafandeh,
Ali Baheri,
Christopher Vermillion
Publication year - 2017
Publication title -
ieee transactions on control systems technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.678
H-Index - 162
eISSN - 1558-0865
pISSN - 1063-6536
DOI - 10.1109/tcst.2017.2779428
Subject(s) - wind speed , wind power , model predictive control , computer science , control theory (sociology) , maximization , gaussian process , turbine , altitude (triangle) , gaussian , control engineering , engineering , meteorology , mathematical optimization , artificial intelligence , aerospace engineering , control (management) , mathematics , geography , electrical engineering , geometry , physics , quantum mechanics
This brief presents a model predictive control (MPC)-based spatiotemporal optimization strategy that is applied to the problem of optimizing the altitude of a type of airborne wind energy (AWE) system, specifically a buoyant airborne turbine. Altitude optimization for AWE systems represents a challenging problem under which the wind speed varies with both time and altitude, is only instantaneously...
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