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A recursive identification framework for rigid-wing airborne wind energy systems enabling robust state and parameter estimation
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DOI：10.1016/j.seta.2026.105119.png)
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Abstract
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• Recursive Identification framework for online state and parameter identification in rigid-wing AWES. • EKF and UKF jointly estimate 44 aerodynamic parameters in crosswind circular flight. • UKF shows smoother convergence and much lower parameter error metrics. • Under measurement noise, UKF stays accurate while offline LS and TLS solutions fail. • Results support onboard real-time aerodynamic model adaptation for rigid-wing AWES.
Keywords:
Airborne wind energy systems
Recursive identification
Extended Kalman filter
Nonlinear systems
Parameter estimation
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