基于随机模型预测控制的卫星编队保持方法  

SATELLITE FORMATION MAINTENANCE BASED ONSTOCHASTIC MODEL PREDICTIVE CONTROL

作　　者：朱琳 龚薇[1] Zhu Lin;Gong Wei(College of Electrical Engineering,Sichuan University,Chengdu 610065,Sichuan,China)

机构地区：[1]四川大学电气工程学院,四川成都610065

出　　处：《计算机应用与软件》2024年第1期42-48,共7页Computer Applications and Software

基　　金：四川省科技厅资助项目(2019YJ0105)。

摘　　要：针对卫星编队队形保持中存在的随机扰动问题,提出一种基于随机模型预测控制(SMPC)的编队构型保持控制算法。在保证精度的情况下,对非线性相对运动力学方程进行线性化离散处理。考虑到模型预测控制不易处理无界随机扰动的机会约束问题,提出有效解决随机变量信息模糊的分布鲁棒机会约束模型,并通过条件风险价值(CVaR)重构机会约束为可处理约束,得到基于随机模型预测控制的队形保持控制算法。通过计算仿真与传统的模型预测控制算法进行对比,验证了该算法的有效性和优越性。Aimed at the problem of random disturbance in formation keeping of satellite formation,a formation configuration keeping control algorithm based on stochastic model predictive control(SMPC)is proposed.Under the condition of ensuring the accuracy,the nonlinear relative motion mechanics equations were linearized and discretized.Considering that model predictive control was not easy to deal with the chance constraint problem of unbounded random disturbance,a distributed robust chance constraint model was proposed to effectively solve the fuzzy information of random variables.The formation keeping control algorithm based on stochastic model predictive control was obtained by reconstructing the chance constraint into a manageable constraint by conditional value at risk(CVaR).The effectiveness and superiority of the algorithm were verified by comparing with the traditional model predictive control algorithm through mathematical simulation.

关 键 词：随机模型预测控制 编队保持 随机扰动 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]