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首页> 外文期刊>Journal of aerospace engineering >Hybrid QPSO and SQP Algorithm with Homotopy Method for Optimal Control of Rapid Cooperative Rendezvous
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Hybrid QPSO and SQP Algorithm with Homotopy Method for Optimal Control of Rapid Cooperative Rendezvous

机译：具有同型方法的混合QPSO和SQP算法，用于快速控制的迅速控制 - Rendezvous

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The fuel-optimal rapid cooperative rendezvous problem between two spacecraft under finite thrust, based on the indirect method, was investigated and converted into a two-point boundary value problem (TPBVP) in this study by using Pontryagin's maximum principle. First, normalization processing of initial costate variables with unknown scopes was carried out to restrict them on a unit hypersphere. The quantum particle swarm optimization (QPSO) algorithm was used to preliminarily search for the initial costate variables of the high-dimensional energy-optimal problem, and then the results obtained were further corrected by the sequence quadratic programming (SQP) algorithm. The preceding combinatorial optimization algorithm with normalization technique considerably increases the probability of finding the approximate initial values of the globally optimal solution. Based on these modified initial costates, the smooth energy-optimal results were transitioned to the desirable nonsmooth fuel-optimal results by the homotopy method. Through the combination of the preceding effective techniques, the following difficulties were successfully overcome: (1) The optimal control was a strongly nonlinear problem under continuous high thrust; (2) in a cooperative rendezvous, the terminal rendezvous orbit was unknown and the parameter variables were doubled, leading to high-dimensional control equations; and (3) the narrow convergence domain of the shooting function made the shooting process extremely sensitive to the initial guess of the costates. The simulation results demonstrate not only the feasibility of the indirect method in solving fuel-optimal cooperative rendezvous, but also the superiority over another orbit transfer optimization method, the hybrid method. (c) 2019 American Society of Civil Engineers.
机译：通过使用Pontryagin的最大原理，研究了在本研究中的有限推力下的两个航天器之间的燃料最佳的快速合作问题，并转化为两点边值问题（TPBVP）。首先，进行了具有未知范围的初始成本变量的归一化处理，以限制在单位过度。量子粒子群优化（QPSO）算法用于预先搜索高维能量最优问题的初始成本变量，然后通过序列二次编程（SQP）算法进一步校正所获得的结果。具有归一化技术的前述组合优化算法显着增加了找到全局最佳解决方案的近似初始值的概率。基于这些改进的初始售价，通过同型方法转变为所需的非光滑燃料 - 最佳结果。通过前述有效技术的组合，成功克服了以下困难：（1）最佳控制是连续高推力下的强烈非线性问题; （2）在合作的Rendezvous中，终端终端轨道未知，参数变量加倍，导致高维控制方程; （3）拍摄功能的窄收敛域使拍摄过程对售价率的初始猜测非常敏感。仿真结果不仅表明了间接方法在解决燃料最佳协作结合的可行性，而且表明了另一种轨道传递优化方法的优越性，混合方法。 （c）2019年美国土木工程学会。

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