Experimental Parameter Identifications of a Quadrotor by Using an Optimized Trajectory

In this document, the parameter identification of a quadrotor is discussed. More precisely, the aim of this paper is to present results on the application of known methods for estimating the dynamic parameters that capture better the behavior of a quadrotor in comparison with the nominal parameters given by the manufacturer. To take into account the limitations of position, velocity, and acceleration of the quadrotor, an optimized trajectory to excite the quadrotor dynamics adequately is obtained. A proportional-integral-derivative (PID) control scheme is used to implement experimentally the tracking of the optimized trajectory. The obtained data is processed off-line to construct the standard and filtered regression models from which the parameter identification is achieved. Specifically, the least-squares and gradient descent algorithms are applied to the regression models giving four sets of estimated parameters. The four sets of parameters obtained in this work are compared with the parameters provided by the manufacturer by computing the error between simulations and experiments. In addition, the output prediction errors of the regression models are computed, thus providing another validation form. All the comparisons show that the estimated parameters are more precise than the nominal ones. The given results support the functionality of the described methodology.