基于改进蜣螂优化的GEO轨道多脉冲追逃博弈

Multi-impulse pursuit-evasion game in GEO based on improved dung beetle optimization

研究了考虑J_(2)摄动、脉冲推力情况下,具有感知延迟的GEO(geosynchronous Earth orbit)轨道追逃博弈问题,建立了综合考虑燃料消耗、单次脉冲速度增量、脉冲时间间隔、任务时长、脉冲数量以及终端距离下的轨道追踪策略优化模型。涉及的优化变量包括脉冲个数、机动时刻序列以及脉冲增量序列。追踪航天器通过多次脉冲追踪目标航天器。为了提高问题求解效率,提出了一种利用Bernoulli混沌映射和最优值引导的改进蜣螂优化算法IBDBO(improved Bernoulli dung beetle optimization),并且为解决终端约束难以满足的问题,引入Lambert机动修正。通过与其他智能算法的对比试验,验证了本算法在收敛速度、收敛稳定性和优化效率上的优势。进而,在一些存在感知延迟的真实场景下的仿真验证了本算法规划追踪策略的有效性,探讨了博弈双方最小距离与目标航天器机动能力以及感知延迟时间之间的因果关系。

This paper investigates the pursuit-evasion game of GEO with J_(2)perturbation and impulsive thrust considering perception delay.An optimization model of orbital pursuit strategy is established,considering fuel consumption,single impulse velocity increment,impulse interval time,mission duration,impulse quantity,and terminal distance.The design variables include the number of impulses,the sequence of maneuver moments,and the sequence of impulse increments.The pursuing spacecraft pursues the target spacecraft through multiple impulses.To enhance problem-solving efficiency,an improved Bernoulli dung beetle optimization algorithm(IBDBO)utilizing Bernoulli chaotic mapping and optimal value guidance is proposed.Additionally,Lambert maneuver correction is introduced to address terminal constraint satisfaction issues.The comparison experiments with other intelligent algorithms verify the superiority of this algorithm in terms of convergence speed,convergence stability and optimization efficiency.Furthermore,simulations in real scenarios with perceptual delay demonstrate the effectiveness of this algorithm for planning pursuit strategies.Finally,the causal relation between terminal distance of both sides in the game and the target spacecraft′s maneuvering capabilities,perception delay time is explored.