Angular Acceleration Estimation in Hybrid INDI Using Extended Kalman Filtering
A. Minafra (TU Delft - Aerospace Engineering)
O. Stroosma – Graduation committee member (TU Delft - Aerospace Engineering)
E. van Kampen – Mentor (TU Delft - Aerospace Engineering)
D. Atmaca – Mentor (TU Delft - Aerospace Engineering)
E. Mooij – Graduation committee member (TU Delft - Aerospace Engineering)
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Abstract
Incremental Nonlinear Dynamic Inversion (INDI) is effective at controlling nonlinear aircraft dynamics by inversion of the control effectiveness matrix, but relies on accurate and time-synchronized measurements of the control input and the state derivative. Hybrid INDI address this limitation by blending sensor measurements with model-based estimates, most commonly through Complementary Filtering. In this work, an Extended Kalman Filter (EKF) is proposed as an alternative angular acceleration estimation method within a Hybrid INDI attitude control framework. A real-time EKF is developed and integrated into the control architecture of a nonlinear aircraft model, and its performance is compared against a baseline Complementary Filter approach.
The parameters of both estimators are tuned using a robust multi-model optimization procedure that accounts for sensor noise, delay, and model-plant uncertainties. Simulation results under nominal and degraded conditions demonstrate that the EKF-based Hybrid INDI approach provides estimation performance comparable to that of the Complementary Filter, with improvements in scenarios of combined sensor noise and delay degradation.