自适应预测补偿的迭代制导方法及其应用研究

针对迭代制导完成后入轨参数或终端程序角修正问题,研究一种基于模型参考的自适应预测补偿迭代制导算法在运载火箭上的应用。该算法在经典迭代制导算法的基础上,根据预测的迭代终端程序角和飞行视加速度的参考模型,对关机点参数进行补偿,依据补偿后的终端指标重新规划飞行轨迹,进而得出满足入轨参数或终端程序角偏差修正的制导指令,提升迭代制导对入轨参数偏差或终端程序角的修正能力。此外,阐述了经典迭代制导的基本算法,概括了自适应预测补偿迭代制导算法的基本原理,并以大推力直接入轨、终端程序角大偏差以及满足终端程序角约束为例,给出相应工况的自适应预测补偿的迭代制导算法。仿真结果表明：该算法对入轨参数和终端程序角偏差具有一定的修正能力。     

Improving the low orbit satellite tracking ability using nonlinear model predictive controller and Genetic Algorithm

The satellite motion on the reference orbit (RO) with less energy consumption has always persuaded researchers to design optimal control systems. The nonlinear nature and time-varying equations of motion make this quest more challenging. The present study proposes a novel control system for satellite motion on the RO by considering a comprehensive model of its dynamics in orbit and a Nonlinear Model Predictive Controller (NMPC). The NMPC calculates the sub-optimal control inputs of satellite motion reference on the elliptic orbit by minimizing a convex cost function at each stage. Moreover, all weighting parameters of the cost function are optimized by the Genetic Algorithm (GA) to produce less perturbation and guarantee the best NMPC performance. Finally, the implemented NMPC has been compared to a Linear MPC (LMPC). The results show that not only can the NMPC resist against larger errors and perturbations, but it can also compensate for those errors by returning the satellite to its main orbit and maintaining it.