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On-line guidance with trajectory constraints for terminal area energy management of re-entry vehicles

机译:带轨迹约束的在线指导,用于可再入车辆的终端区域能量管理

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In this article, an on-line guidance strategy for terminal area energy management phase of a re-entry flight is proposed. In order to fulfil the objectives of this flight phase, the algorithm continuously performs long- and short-term on-line trajectory generation, also accounting for the most relevant vehicle and trajectory constraints. Long-term guidance computes a reference trajectory which minimizes the distance from the final target. Short-term guidance generates the control commands by computing a traj ectory that minimizes the displacement from the reference one, thus compensating for the errors due to the environmental disturbances and to the uncertainties of the vehicle model. In the proposed guidance strategy, the main vehicle performance constraints are appropriately accounted for, thus guaranteeing adaptivity in the failure situations where the manoeuvring capabilities are reduced. The proposed guidance strategy has been developed in the framework of the unmanned space vehicle program of the Italian Aerospace Research Centre for the execution of Dropped Transonic Flight Test second mission. In this article, the algorithm performances and robustness to the vehicle initial state have been assessed through a preliminary Monte Carlo analysis. Furthermore, several simulations with bank angle and angle of attack limitations have shown the effectiveness of the algorithm in the presence of reduced manoeuvring capabilities.
机译:在本文中,提出了一种用于再入飞行的终端区能量管理阶段的在线指导策略。为了实现该飞行阶段的目标,该算法连续执行长期和短期的在线轨迹生成,还考虑了最相关的飞行器和轨迹约束。长期制导计算出一个参考轨迹,该轨迹使距最终目标的距离最小。短期制导通过计算使与参考基准的位移最小的轨迹来生成控制命令,从而补偿由于环境干扰和车辆模型的不确定性引起的误差。在提出的制导策略中,主要车辆性能约束得到了适当考虑,从而保证了在机动能力降低的故障情况下的适应性。拟议的指导策略是在意大利航空航天研究中心的无人飞行器计划的框架内制定的,用于执行“超音速飞行下降试验”的第二次飞行任务。在本文中,通过初步的蒙特卡洛分析评估了算法性能和对车辆初始状态的鲁棒性。此外,一些具有倾斜角和攻角限制的仿真表明,该算法在机动能力降低的情况下是有效的。

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