基于分布式滚动时域的飞行器集群打击任务轨迹优化

Trajectory Optimization for Aircraft Swarms Strike Missions Based on Distributed Receding Horizon

  • 摘要: 为提升飞行器集群在动态对抗环境中实施协同饱和打击时的实时轨迹规划能力,提出一种融合多段伪谱法与滚动时域优化的决策方法。首先,基于飞行器动力学模型,考虑性能约束、集群间距离约束以及避障约束等条件,构建任务目标抵近、攻击角度偏差最小和时间协同的飞行器集群协同打击任务多目标优化问题,建立集群轨迹优化问题模型。其次,通过精确罚函数将非线性约束增广到目标函数中处理,以进一步提高优化问题的求解速度。最后,使用多段伪谱法滚动求解上述集群轨迹优化问题。为了验证所提方法的有效性,本文想定飞行器集群协同打击动态目标任务场景,通过数值仿真实验结果表明:飞行器集群能躲避威胁区,饱和打击动态任务目标,所提出的方法计算速度快(平均优化耗时小于0.5 s),具备在线轨迹优化能力。

     

    Abstract: To enhance the real-time trajectory planning capability of aircraft swarms in dynamic and antagonistic environments for cooperative saturation attacks, a decision-making approach integrating a multiphase pseudospectral method with receding horizon optimization is proposed. Firstly, a multi-objective optimization problem for cooperative strike missions of aircraft swarms is formulated based on the aircraft dynamics model, where the constraints such as performance limits, inter-swarm distance, and obstacle avoidance are considered, and the terms of target-approach, attack angle deviation minimization, and time synchronization are incorporated. Thereby a model of swarm trajectory optimization problem is established. Secondly, nonlinear constraints are systematically augmented into the objective function through exact penalty functions to further accelerate the solution process of the optimization problem. Finally, the multiphase pseudospectral method is employed in a receding horizon framework to iteratively solve the aforementioned swarm trajectory optimization problem. To validate the effectiveness of the proposed method, a scenario of aircraft swarm cooperatively striking dynamic targets is simulated. Numerical simulation results show that the aircraft swarm successfully avoids threat zones and achieves saturation strikes on dynamic targets. The proposed method features rapid computation speed (with an average optimization time of less than 0.5 s), demonstrating its capability for online trajectory optimization.

     

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