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Trajectory tracking for fixed-wing UAV using model predictive control and adaptive backstepping

机译：基于模型预测控制和自适应反推的固定翼无人机航迹跟踪

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This paper presents a two layer guidance and control system design for fixed-wing unmanned aerial vehicles (UAV). On the top level, the guidance system makes the airplane follows precomputed references using a novel iterative model predictive scheme, which can handle the nonlinear optimization problem by successive linearizations (starting the algorithm using a robust L1 navigation law which ensures the availability of the solution). The outputs of this algorithm are references in airspeed, flight path angle and bank angle, which are seek by the low level controller also presented in this paper. This controller uses an adaptive backstepping approach for the longitudinal dynamics, and a conventional integral-LQR controller for the lateral-directional dynamics. Simulations show good performances of the overall architecture.
机译：本文提出了一种用于固定翼无人机的两层制导与控制系统设计。在顶层，制导系统使用新颖的迭代模型预测方案使飞机遵循预先计算的参考值，该方案可以通过连续的线性化处理非线性优化问题（使用鲁棒的L1导航定律启动算法，以确保解决方案的可用性） 。该算法的输出是空速，飞行路径角和倾斜角的参考值，这些参考值也由本文介绍的低级控制器来寻找。该控制器对纵向动力学采用自适应反推方法，而对横向动力学采用常规的积分LQR控制器。仿真显示了整体架构的良好性能。

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