Model Identification and ℋ∞ Attitude Control for Quadrotor MAV's

This paper presents the results of modelling, parameter identification and control of the rotational axes of a quadrotor robot. The modelling is done in Newton-Euler Formalism and has been published before. Contrarily, our method uses a Grey-Box-based, iterative parameter identification approach, the results of which can easily be reproduced and offers great accuracy. By neglecting nonlinear and cross-coupling effects, only three to four parameters have to be identified per axis, depending on the order of the motor dynamics. Based on the achieved results we were able to design an aggressive $\mathcal{H_{\infty}}$ attitude controller, which shows superior performance to the normal PID-like controllers. With an anti-windup compensator based on Riccati---equations we are able to show exceptional input disturbance rejection, even with disturbances saturating the engines.