卫星运载火箭迭代制导方案

F. Ashraf, Ashmal Shafique, A. Shahzad
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引用次数: 2

摘要

本文的目的是通过与最优控制算法的比较,实现并确定高轨道迭代制导算法的最优性。SLV制导的目标是确保SLV按照其任务轮廓将给定的有效载荷注入其轨道,这也是在发射前无法可靠地预测或预测的各种扰动和其他参数变化存在的情况下。这些参数变化包括推进系统性能、发射日风、重量和其他大气参数,如密度和温度的不确定性。本文讨论了迭代算法在大气外相位的实现,以实时提供近最优制导。制导在惯性二维参考系和闭环仿真中进行,其中输入来自机载导航系统;制导也是在飞行器的最后一级进行的。该算法首先在重力均匀的平坦地球表面上建立了运载火箭的运动方程,然后将其推广到重力服从平方反比律的球形地球模型上。控制向量作为飞行器状态变量的函数进行计算,制导命令在每个制导周期结束时使用当前状态变量进行更新。为了检验算法的最优性,利用最优控制理论对同一问题进行了求解,并对结果进行了比较。利用庞特里亚金最小值原理将最优控制问题转化为两点边值问题。这两种算法都在MATLAB/SIMULINK上实现。仿真和比较结果表明,迭代制导方法具有较高的精度,在任何扰动下都能保持其最优特性。因此,迭代制导方案对于运载火箭的实时制导是一种非常可靠和有效的方法,因为单个制导回路所需的执行时间都在实时实现的范围内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iterative Guidance Scheme for Satellite Launch Vehicles
The purpose of this paper is to implement and ascertain the optimality of the Iterative Guidance Algorithm for higher altitude orbits by comparing it with the Optimal Control Algorithm. The objective of SLV guidance is to ensure that the SLV injects the given payload into its orbit, as specified by its mission profile, that too in the presence of various kind of perturbations and other parametric variations which cannot be reliably anticipated or predicted before the launch. These parametric variations include propulsion system performance, launch day winds, weight and other atmospheric parameters like density and temperature uncertainties. This paper discusses the implementation of iterative algorithm in an exo-atmospheric phase to provide near optimal guidance in real-time. The guidance is carried out in an inertial 2-D reference frame and a closed loop simulation in which inputs are taken from the on-board navigation system; also the guidance is carried out in the last stage of the vehicle. In the algorithm, the equations of motion of the launch vehicle are first taken for a flat earth surface with the gravity field being uniform, then those equations are extended over a spherical earth model where gravity follows the inverse square law. The control vector is computed as a function of the state variables of the vehicle and the guidance commands are updated at the end of each guidance cycle using the current state variables. In order to check the optimality of the algorithm, the same problem is solved using the Optimal Control Theory and the results are compared. The optimal control problem is converted into a two-point boundary value problem using Pontryagin’s Minimum Principle. Both the algorithm’s are implemented on MATLAB/SIMULINK. Simulation results and the comparisons show that the iterative guidance approach gives highly accurate results and retains its optimal properties under any kind of perturbation. Hence, the iterative guidance scheme is a very reliable and effective method of guidance for a launch vehicle in real-time as the results indicate that the execution time that is required for a single guidance loop stays within the domain of real-time implementation.
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