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Robust Bang-Off-Bang Low-Thrust Guidance Using Model Predictive Static Programming

机译:使用模型预测静态编程强大的Bang-Off-Bang-Thrust指导

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Model Predictive Static Programming (MPSP) has been always used under the assumption of continuous or impulsive control, but never in low-thrust transfers featuring bang-off-bang control. Following the observation that the sensitivity matrix (SM) is discontinuous across the switching time, this work introduces a two-loop MPSP guidance scheme using fuel-optimal trajectories as nominal solutions. In our method, the equations of motion are augmented by the mass costate equation, while the velocity costate is the MPSP control, expressed by a weighted sum of Fourier basis functions. The SM is computed at the switching time by using calculus of variations. Both the MPSP control and the initial mass costate are updated in an inner loop using Newton's method, and continuation is employed in an outer loop to face large perturbations. A sample interplanetary CubeSat mission to an asteroid is used as study case to illustrate the effectiveness and robustness of the method developed.
机译:模型预测静态编程(MPSP)始终在连续或冲动控制的假设下使用,但从未在低推力转移以BANC-OFF-BAND控制中使用。在观察到敏感性矩阵(SM)在切换时间上不连续,这项工作引入了使用燃料最佳轨迹作为标称解决方案的双环MPSP指导方案。在我们的方法中,运动的方程由大量成本速度方程增强,而速度速度是MPSP控制,由傅立叶基函数的加权之和表示。通过使用变化的微积分在切换时间来计算SM。 MPSP控制和初始质量速度都在使用牛顿的方法中更新在内​​圈中,并且继续在外环中采用以面对大的扰动。将样品截然型立方体立方体使命用于小行星的任务用作研究表壳,以说明该方法的有效性和稳健性。

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