6533b7d6fe1ef96bd1265d78

RESEARCH PRODUCT

Wind Shear On-Line Identification for Unmanned Aerial Systems

Caterina GrilloManoela PattiFernando Montano

subject

Wind shear System Identification Unmanned Aerial SystemsEngineeringbusiness.industryCovariance matrixState vectorSettore ING-IND/03 - Meccanica Del VoloFilter (signal processing)Parameter identification problemExtended Kalman filterControl theoryRobustness (computer science)Wind shearState spacePharmacology (medical)business

description

An algorithm to perform the on line identification of the wind shear components suitable for the UAS characteristics has been implemented. The mathematical model of aircraft and wind shear in the augmented state space has been built without any restrictive assumption on the dynamic of wind shear. Due to the severe accelerations on the aircraft induced by the strong velocity variation typical of wind shear, the wind shear effects have been modeled as external forces and moments applied on the aircraft. The identification problem addressed in this work has been solved by using the Filter error method approach. An Extended Kalman Filter has been developed to propagate state. It has been tuned by using a database of measurements through off-line identification of the process noise covariance matrix. Afterwards the implemented EKF has been employed to estimate onboard either aircraft state or turbulence, with significant savings in terms of time and computing resources. Robustness of implemented algorithm has been verified by means of several tests. The obtained results show the feasibility of the tuned up algorithm. In fact it is possible, by using a few numbers of low cost sensors, to estimate with a noticeable accuracy the augmented state vector. Besides a very short computation time is required to perform the augmented state estimation even by using low computation power.

yearjournalcountryeditionlanguage
2014-07-01
http://hdl.handle.net/10447/147395