基于态势趋势评估的带干扰双启发式动态规划武装直升机武器/飞行综合控制。

IF 6.5
Zeyu Zhou, Yuhui Wang, Qingxian Wu
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引用次数: 0

摘要

为提高武装直升机自主空战能力,提出了一种基于启发式动态规划(HDP)算法的干扰下武器/飞控动态集成设计方法。针对直升机欠驱动、高耦合、非线性的特点,提出了一种结合武器投送旋转的数学模型,以实现精确瞄准和降低控制器复杂度。为实现目标与直升机的动态博弈,引入了瞄准偏差和攻击占用两个关键指标。虽然一般态势评估侧重于当前空战信息,但拟议的态势趋势评估集成了当前数据和未来机动趋势,影响直升机和目标的后续运动。在此理论框架的基础上,推导了目标和直升机的近最优策略。为了提高直升机的空战性能,提出了一种基于辨识和HDP算法的干扰下直升机最优控制策略。识别过程有效地消除了训练估计误差,而HDP算法保证了有界性、单调性、收敛性和最优性。仿真实验证实了所提出的控制方法在解决武器/飞行控制一体化设计挑战方面的有效性和实用性,展示了自主空战性能的显著提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated weapon/flight control for armed helicopters based on situation trend assessment via dual heuristic dynamic programming with disturbances.

Aiming to enhance autonomous air combat capabilities for armed helicopters, a novel dynamic integrated weapon/flight control design method is proposed in the presence of disturbances based on a heuristic dynamic programming (HDP) algorithm. Driven by the underactuated, highly coupled, nonlinear characteristics of helicopters, the proposed mathematical model incorporates weapon delivery rotation to achieve precise aiming and reduce controller complexity. To realize dynamic gaming of the target and the helicopter, two critical indexes are introduced: aiming deviation and attack occupation. While general situation assessment focuses on current air combat information, the proposed situation trend assessment integrates both current data and future maneuver trends, influencing the subsequent movements of both the helicopter and the target. Based on this theoretical framework, near-optimal strategies for both the target and the helicopter are derived. Furthermore, for better air combat performance, this paper proposes an optimal control policy for helicopters based on an identification and an HDP algorithm under disturbances. The identification process effectively eliminates training estimation errors, while the HDP algorithm ensures boundedness, monotonicity, convergence, and optimality. Simulation experiments confirm the efficacy and practicality of the proposed control methods in addressing the challenges of integrated weapon/flight control design, demonstrating significant improvements in autonomous air combat performance.

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