基于后退地平线控制的运载火箭上升制导

Qianwei He, Ye Yang, Lei Liu, Zhongtao Cheng
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摘要

针对运载火箭上升阶段未知扰动所带来的困难和挑战,研究了一种基于粒子群优化(PSO)算法的后退地平线控制(RHC)框架轨迹跟踪策略。由于RHC在每一步都解决在线优化问题,因此计算可能会很耗时。为了加快RHC的计算速度,将在线优化问题转化为一维变量优化问题,并利用粒子群算法求解控制动作。以毫秒为单位提供求解时间,保证了RHC控制器的可行性。仿真结果表明,该策略不仅能满足较快的计算速度,而且在存在气动不确定性、推力不确定性和过程约束的情况下也能实现较好的性能。
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Ascent Guidance for Launch Vehicle Based on Receding Horizon Control
For the difficulties and challenges caused by the unknown disturbance during the ascent stage of the launch vehicle, a trajectory tracking strategy using particle swarm optimization (PSO) algorithm in a receding horizon control (RHC) framework is investigated in this paper. Since the RHC solves the online optimization problem at each step, the calculations can be time-consuming. To speed up the computation of RHC, the online optimization problem is transformed into a one-dimensional variable optimal problem and the control actions are obtained by PSO. Providing solve times in milliseconds, which guarantees the feasibility of the RHC controller. Simulation results are provided to illustrate that this strategy can not only satisfy the fast calculation speed, but also can realize better performance with the existence of aerodynamic uncertainty, thrust uncertainty, and process constraint.
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