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Optimal FPID Control Approach for a Docking Maneuver of Two Spacecraft: Translational Motion

机译:两种航天器对接机动的最优FPID控制方法:平移运动

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This paper studies the use of a fuzzy proportional integral derivative (PID) controller based on a genetic algorithm (GA) in a docking maneuver of two spacecraft in the space environment. The docking maneuver consists of two parts: translation and orientation. To derive governing equations for the translational phase, Hill linear equations in a local vertical-local horizontal (LVLH) frame will be used. In fuzzy PID (FPID) controller design, two fuzzy inference motors will be utilized. The single input fuzzy inference motor (SIFIM) is the first to have only one input, and for each state variable, a separate SIFIM is defined. Another fuzzy inference motor, the preferrer fuzzy inference motor (PFIM), represents the control priority order of each state variable and a supervisory role in large deviations. This FPID controller covers a servicer's translation of a docking maneuver, which tries to dock with a stable nonrotating target. Various conflicting objective functions are distance errors from the set point and control efforts. To enter the control limit in an optimization problem, the maximal value of the thrust force is constrained. Considering these objective functions, a statistical analysis on the GA parameters will be performed, and the test with the best minimum fuel consumption and minimum deviations of the servicer from the equilibrium point will be chosen as the best test. The three-dimensional (3D) Pareto frontiers corresponding to the best test will be plotted, and the optimal points related to the objective functions will be demonstrated on them; the time response figures corresponding to these points will then be generated. The results prove that this controller shows an efficient performance in the docking maneuver of the servicer spacecraft. In comparison with similar work, a number of system performance parameters (e.g., settling time) will be improved, and overshoot (as a critical parameter in docking maneuver) will be truncated. (C) 2017 American Society of Civil Engineers.
机译:本文研究了基于遗传算法(GA)的模糊比例积分微分(PID)控制器在两个航天器在空间环境中对接机动中的使用。对接操作包括两个部分:平移和定向。为了导出平移阶段的控制方程,将使用局部垂直-局部水平(LVLH)框架​​中的Hill线性方程。在模糊PID(FPID)控制器设计中,将使用两个模糊推理电机。单输入模糊推理电动机(SIFIM)是第一个仅具有一个输入的电动机,并且为每个状态变量定义了一个单独的SIFIM。另一个模糊推理电动机,首选模糊推理电动机(PFIM)代表每个状态变量的控制优先级顺序,并在较大偏差中起监督作用。该FPID控制器涵盖了服务人员对接操作的翻译,该操作试图与稳定的非旋转目标对接。各种相互矛盾的目标功能是距离设定点和控制努力的距离误差。为了在优化问题中输入控制极限,必须限制推力的最大值。考虑到这些目标函数,将对GA参数进行统计分析,并选择具有最佳最小燃油消耗和服务员与平衡点的最小偏差的测试作为最佳测试。将绘制与最佳测试相对应的三维(3D)帕累托边界,并在其上展示与目标函数相关的最佳点;然后将生成与这些点相对应的时间响应图。结果证明,该控制器在服务航天器的对接操纵中显示出有效的性能。与类似工作相比,将改善许多系统性能参数(例如建立时间),并会截断过冲(作为对接操作中的关键参数)。 (C)2017年美国土木工程师学会。

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