We propose a disturbance observer-based controller to deal with the trajectory tracking problem of a quadrotor subject to parametric uncertainties and wind disturbance. The design is based on the combination of a recursive robust linear-quadratic regulator and a Kalman filter. Robust regulation deals with uncertainties of state and input matrices of the quadrotor in order to minimize, mainly, its trajectory tracking error. Filtering aims to estimate wind disturbance based on an augmented state-space model of the quadrotor. We finish the approach with a compensation controller whose task is to perform disturbance attenuation. We develop indoor experiments where a wind disturbance source provides a measurable speed pattern. We provide a comparative study among the robust control approach proposed with a feedback linearization controller, a proportional-integral-derivative controller, and a nominal linear-quadratic regulator.

No abstract

Over the last decade, the rapid evolution in communications technology, mechanics and electronics has propelled access to Unmanned Aerial Vehicles (UAVs). Among this class of robots, quadrotors stand out due to maneuverability and Vertical Take Off and Landing (VTOL) capability. This work proposes a methodology to solve the model parameter estimation problem of a commercial quadrotor. Mathematical models are derived and implementation details are given. Experimental results, obtained in an open source environment associated with a motion capture system, verify that the estimated dynamic model approximates to the real dynamics.