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首页> 外文期刊>Aerospace >Trajectory Planning in Time-Varying Adverse Weather for Fixed-Wing Aircraft Using Robust Model Predictive Control
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Trajectory Planning in Time-Varying Adverse Weather for Fixed-Wing Aircraft Using Robust Model Predictive Control

机译：基于鲁棒模型预测控制的固定翼飞机时变不利天气下的航迹规划

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摘要

The avoidance of adverse weather is an inevitable safety-relevant task in aviation. Automated avoidance can help to improve safety and reduce costs in manned and unmanned aviation. For this purpose, a straightforward trajectory planner for a single-source-single-target problem amidst moving obstacles is presented. The functional principle is explained and tested in several scenarios with time-varying polygonal obstacles based on thunderstorm nowcast. It is furthermore applicable to all kinds of nonholonomic planning problems amidst nonlinear moving obstacles, whose motion cannot be described analytically. The presented resolution-complete combinatorial planner uses deterministic state sampling to continuously provide globally near-time-optimal trajectories for the expected case. Inherent uncertainty in the prediction of dynamic environments is implicitly taken into account by a closed feedback loop of a model predictive controller and explicitly by bounded margins. Obstacles are anticipatory avoided while flying inside a mission area. The computed trajectories are time-monotone and meet the nonholonomic turning-flight constraint of fixed-wing aircraft and therefore do not require postprocessing. Furthermore, the planner is capable of considering a time-varying goal and automatically plan holding patterns.
机译：避免不利天气是航空业不可避免的与安全相关的任务。自动避让可以帮助提高安全性并降低载人和无人航空的成本。为此，提出了一种针对移动障碍中的单源单目标问题的简单轨迹规划器。基于雷暴临近预报，在具有时变多边形障碍物的几种情况下解释并测试了该功能原理。此外，它还适用于非线性移动障碍物中的所有非完整规划问题，这些障碍物的运动无法解析地描述。提出的解决方案完全的组合计划器使用确定性状态采样为预期情况连续提供全局的近时间最优轨迹。模型预测控制器的闭合反馈回路隐含地考虑了动态环境预测中的固有不确定性，而边界裕量则明确地考虑了固有不确定性。在任务区域内飞行时，可以避免障碍物。计算的轨迹是时间单调的，并且满足固定翼飞机非完整的转弯飞行约束，因此不需要后处理。此外，计划者能够考虑时变的目标并自动计划持有方式。

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