The paper proposes two control methods for performing a backflip maneuver with miniature quadcopters. First, an existing feedforward control approach is improved by finding the optimal sequence of motion primitives via Bayesian optimization, using a surrogate Gaussian Process model. To evaluate the cost function, the flip maneuver is performed repeatedly in a simulation environment. The second method is based on closed-loop control and it consists of two main steps: first a novel robust, adaptive controller is designed to provide reliable reference tracking even in case of model uncertainties. The controller is constructed by augmenting the nominal model of the drone with a Gaussian Process that is trained by using measurement data. Second, an efficient trajectory planning algorithm is proposed, which designs feasible trajectories for the flip maneuver by using only quadratic programming. The two approaches are analyzed in simulations and in real experiments using Bitcraze Crazyflie 2.1 quadcopters.

翻译：本文针对微型四旋翼飞行器后空翻机动动作，提出了两种控制方法。首先，通过贝叶斯优化方法并借助高斯过程代理模型，寻找最优运动基元序列，从而改进了一种现有的前馈控制方法。为评估代价函数，需在仿真环境中反复执行后空翻机动。第二种方法基于闭环控制，包含两个主要步骤：首先设计一种新型鲁棒自适应控制器，即便存在模型不确定性，仍能提供可靠的参考跟踪性能。该控制器通过在无人机标称模型上叠加一个基于测量数据训练的高斯过程进行构建。其次，提出一种高效的轨迹规划算法，仅需使用二次规划即可为后空翻机动设计可行轨迹。通过仿真实验及基于Bitcraze Crazyflie 2.1四旋翼飞行器的实物实验，对两种方法进行了分析。