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Many multirotor Unmanned Aerial Systems applications have a critical need forprecise position control in environments with strong dynamic externaldisturbances such as wind gusts or ground and wall effects. Moreover, tomaximize flight time, small multirotor platforms have to operate within strictconstraints on payload and thus computational performance. In this paper, wepresent the design and experimental comparison of Model Predictive and PIDmultirotor position controllers augmented with a disturbance estimator toreject strong wind gusts up to 12 m/s and ground effect. For disturbanceestimation, we compare Extended and Unscented Kalman filtering. In extensivein- and outdoor flight tests, we evaluate the suitability of the developedcontrol and estimation algorithms to run on a computationally constrainedplatform. This allows to draw a conclusion on whether potential performanceimprovements justify the increased computational complexity of MPC formultirotor position control and UKF for disturbance estimation.

Disturbance Estimation and Rejection for High-Precision Multirotor Position Control