Wind estimation algorithm for quadrotors using detailed aerodynamic coefficients

Abstract

In the context of safe control of quadrotors, wind velocity estimation and compensation have a key-role. For this reason, assuming the lack of airspeed sensors and considering sensors noise, in this paper three time-varying parameter estimation algorithms are introduced, studied and merged to estimate the varying wind velocity, using only on-board quadrotor sensors and an inertial tracking position system (e.g. Optitrack camera, GPS). To this end, a detailed quadrotor flight dynamics model is presented using identified aerodynamic coefficients and wind velocity components along the three axes. Then, a decomposition of dynamical equations is performed in known and unknown terms to be estimated. Thanks to this decomposition, the estimation algorithms are built and finally tested and validated in numerical experiments, against the introduced sensors' noise.

Trajectory tracking for a quadrotor under wind perturbations: sliding mode control with state-dependent gains

“…whereK D = KK D . In the earth frame using the rotation matrix (3) and the upper bound for the disturbances (17), (18), (19) it becomes…”

“…The closed-loop system stability is ensured for a selected maximum admissible value of the wind speed. The control strategy proposed in this article can be equipped with an additional wind estimator algorithm, as in [18], reducing automatically the control effort on the rotors when it is not necessary. However the peculiarity of the proposed SMC approach design is that the control allows the UAV to remain stable even without any coupled external disturbance observer.…”

On sliding mode control design for UAV using realistic aerodynamic coefficients

“…The closed-loop system stability is ensured for a selected maximum admissible value of the wind speed. The proposed in this article control strategy can be equipped with an additional wind estimator algorithm, as in [1], reducing automatically the control effort on the rotors when it is not necessary.…”

“…which come out from the on-board wind estimator explained in [1]. Taking into account the proposed model equations…”

“…The objective is to build a robust altitude and attitude nonlinear controller for a small UAV with a limited knowledge of the wind perturbation. The aerodynamic model described in this article can be used to estimate wind speed as in [1], the estimated values can be used in the control to properly adapt the gains on-line. …”