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Boost-Phase Trajectory Planning with the Nonregular Reachable Area Constraints
International Journal of Aerospace Engineering ( IF 1.1 ) Pub Date : 2022-06-26 , DOI: 10.1155/2022/9443050
Yin Diao 1 , Rongjun Mu 1 , Yingzi Guan 1 , Naigang Cui 1
Affiliation  

During emergency return or mission change, the boost-glide vehicle needs to meet the nonregular reachable area constraints (NRACs). Therefore, this paper introduced NRACs into boost-phase trajectory planning to extend the maneuvering range and enhance the mission adaptability of boost-glide vehicle. Firstly, the library of the reachable area boundaries was constructed with the fast computation method under the deviations of boost terminal states, and the polynomials were used to fit the boundary parameters. Secondly, the nonlinear mapping relationship between the reachable area boundary parameters and the deviations of boost terminal states was obtained by the deep neural networks (DNNs). Then, the new boundary parameters were obtained by the constraint transformation rules under NRACs and the separation window constraints and transformed into the constraints of the boost-phase terminal states by DNNs. Finally, the hp-adaptive pseudospectral method (hpPM) was adopted to complete the trajectory planning considering the path and terminal constraints. The simulation results showed that the proposed trajectory planning method considering NRACs had high trajectory planning accuracy and good deviation adaptability and exhibited excellent performance in the adjustment of reachable area. This study provides theoretical support for integrate mission decisions and trajectory planning of boost-glide vehicles.

中文翻译:

具有非规则可达区域约束的提升阶段轨迹规划

在紧急返回或任务变更期间,助推滑翔飞行器需要满足非常规可达区域约束(NRAC)。因此,本文将NRACs引入助推阶段轨迹规划,以扩大机动范围,增强助推滑翔飞行器的任务适应性。首先,在boost终端状态偏差下,采用快速计算方法构建可达区域边界库,并使用多项式拟合边界参数。其次,通过深度神经网络(DNNs)获得可达区域边界参数与提升终端状态偏差之间的非线性映射关系。然后,新的边界参数通过NRACs下的约束变换规则和分离窗口约束得到,并通过DNNs转化为boost阶段终端状态的约束。最后,采用hp自适应伪谱方法(hpPM)完成考虑路径和终端约束的轨迹规划。仿真结果表明,所提出的考虑NRACs的轨迹规划方法具有较高的轨迹规划精度和良好的偏差适应性,在可达区域调整中表现出优异的性能。该研究为助推滑翔飞行器的综合任务决策和轨迹规划提供了理论支持。采用hp自适应伪谱方法(hpPM)完成考虑路径和终端约束的轨迹规划。仿真结果表明,所提出的考虑NRACs的轨迹规划方法具有较高的轨迹规划精度和良好的偏差适应性,在可达区域调整中表现出优异的性能。该研究为助推滑翔飞行器的综合任务决策和轨迹规划提供了理论支持。采用hp自适应伪谱方法(hpPM)完成考虑路径和终端约束的轨迹规划。仿真结果表明,所提出的考虑NRACs的轨迹规划方法具有较高的轨迹规划精度和良好的偏差适应性,在可达区域调整中表现出优异的性能。该研究为助推滑翔飞行器的综合任务决策和轨迹规划提供了理论支持。
更新日期:2022-06-27
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