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• W3012169223 abstract "This paper applies a unique variant of point-to-point iterative learning control, wherein total iteration times are made flexible in order to truly maximize an economic performance index, to the problem of crosswind flight control in an airborne wind energy system. The mathematical formulation relies on a lifted system representation that is specified without explicit reference to time, along with relaxed waypoint following constraints (termed region-to-region constraints) that ultimately allow for flexible waypoint arrival times. The approach is applied to a simplified 2D model of an airborne wind energy system that executes repetitive crosswind motions with the ultimate (economic) goal of maximizing its net energy output." @default.
• W3012169223 created "2020-03-23" @default.
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• W3012169223 date "2019-12-01" @default.
• W3012169223 modified "2023-10-18" @default.
• W3012169223 title "Flexible-Time Economic Iterative Learning Control: A Case Study in Airborne Wind Energy" @default.
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• W3012169223 doi "https://doi.org/10.1109/cdc40024.2019.9029557" @default.
• W3012169223 hasPublicationYear "2019" @default.
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