操纵性弱的滑翔制导射弹的鲁棒轨迹规划

Qiulin Yin, Qi Chen, Zhongyuan Wang, Qinghai Wang
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摘要

由于发射平台和成本的限制,滑翔制导弹丸的机动性能有限,因此必须合理设计弹道方案。为了降低弹道方案对不确定因素的敏感性,同时保证飞行方案与制导控制系统的兼容性,充分发挥弹丸的控制能力,提出了一种闭环鲁棒弹道规划方法。建立了主要不确定因素模型和控制起点状态偏差模型。基于 NIPCE 方法,将随机动态模型转化为以 PCE 系数为状态变量的高维确定性模型,并得到不确定性传播规律。采用 PID 算法设计基于位置误差反馈的跟踪制导法则,并建立相应的开环和闭环鲁棒轨迹规划模型。利用直射法将其转化为非线性编程问题,从而解决了最优控制问题。仿真结果表明,NIPCE 方法能在保证精度的同时显著提高不确定性传播的计算效率;与并行 MCS 相比,计算时间缩短了 96.8%。开环鲁棒规划能有效降低滑翔轨迹对不确定性的敏感性(与确定性规划相比,末端高度和横向偏差的标准偏差分别降低了 23.6% 和 35.3%),但不能完全消除末端离散。在开环规划的基础上,闭环鲁棒规划有效地改善了控制功耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Trajectory Planning of Gliding-Guided Projectiles with Weak Maneuverability
Due to constraints in launch platforms and cost, the maneuverability of gliding-guided projectiles is limited, necessitating a rational design of their trajectory schemes. To reduce the sensitivity of trajectory schemes to uncertainties while ensuring compatibility between flight schemes and guidance control systems and fully exploiting the control capability of the projectile, a closed-loop robust trajectory planning method is proposed. Models of major uncertain factors and state deviation at the control start point are established. Based on the NIPCE method, the stochastic dynamic model is transformed into a high-dimensional deterministic model with PCE coefficients as state variables, and the uncertainty propagation law is obtained. A PID algorithm is employed to design a tracking guidance law based on position error feedback, and open-loop and closed-loop robust trajectory planning models are established accordingly. The optimal control problem is solved by transforming it into a nonlinear programming problem using the direct shooting method. Our simulation results indicate that the NIPCE method can significantly improve the computational efficiency of uncertainty propagation while ensuring accuracy; compared with parallel MCS, the computation time is reduced by 96.8%. Open-loop robust planning can effectively mitigate the sensitivity of gliding trajectories to uncertainties (the standard deviations of terminal altitude and lateral deviations are reduced by 23.6% and 35.3%, respectively, compared to deterministic planning) but cannot completely eliminate terminal dispersion. Closed-loop robust planning effectively improves control effort consumption on the basis of open-loop planning.
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