Linear Parameter-Varying (LPV) system based hybrid loads observer using an uncertain aircraft model

The hybrid loads observer has consistently demonstrated its effectiveness in precisely estimating structural loads and wind disturbances in prior applications. This level of precision is attained through the combination of a high-fidelity physical, nonlinear flight dynamics model with a data-driven correction model. To mitigate the typically high computational effort, the nonlinear model of the loads observer is substituted in this work with a linear parameter-varying (LPV) system while preserving a comparable level of accuracy of the hybrid observer. For this purpose, the model is approximated by scheduled Linear Time-Invariant (LTI) models derived from Jacobian linearization of the nonlinear model. The robustness of this linear parameter-varying hybrid approach against parameter uncertainties is evaluated through virtual flight test studies using the subscale test aircraft Wingfinity-BL as an application example. It is demonstrated that increased model uncertainties lead to a reduction in wind estimation accuracy of the hybrid loads observer. Additionally, increased parameter uncertainties adversely affect the quality of structural loads estimation within the model-based (physical) approach of the observer. Nonetheless, this loss of accuracy can be effectively compensated by the data-driven correction model, leading to a high degree of loads estimation accuracy. Finally, experimental data from a wind tunnel test campaign, utilizing a 1-DOF representative test wing of the aircraft, confirms the high estimation accuracy of the LPV-based hybrid loads observer. Despite employing low-fidelity models, achieving high accuracy is feasible while maintaining the characteristic low complexity of the correction model.

DDC Class

690: Building, Construction

620: Engineering

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Linear Parameter-Varying (LPV) system based hybrid loads observer using an uncertain aircraft model