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Automatic EKF Tuning for UAS Path Following in Turbulent Air

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By using two simultaneously working Extended Kalman Filters, a procedure is implemented in order to perform in a fully autonomous way the path following in turbulent air. To guarantee the robustness of the proposed algorithm, an automatic tuning procedure is proposed to determine optimal values of Process and Measurement Noise statistics. Such a procedure is based on both the characteristics of the disturbances and the desired flight path; in particular, a specific performance index is applied to tune filters. In this way control laws are adapted to the flight condition and these lead to an optimal path-following. This research represents an upload of previous papers. It allows eliminating the time expensive trial and error procedure usually employed to tune Extended Kalman Filters. Obviously, procedure results are optimal for ever flight condition.
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Adaptive Control Laws; Extended Kalman Filter; Trajectory Tracking; Control Optimization

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