基于MRAS的卫星姿态控制系统鲁棒模型预测控制

F. Pirouzmand, N. Ghahramani
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引用次数: 9

摘要

提出了一种基于模型参考自适应系统的鲁棒模型预测控制方法。在该算法中,利用MRAS设计了一种三自由度卫星组合RMPC控制器,补偿了惯性矩不确定性和外界干扰对闭环系统稳定性和性能的影响。控制律是一种状态反馈,其增益是通过求解一个包含若干线性矩阵不等式的凸优化问题得到的。为避免致动器饱和,在优化问题中引入线性矩阵不等式作为LMI。该算法的优点是不需要从系统模型中获取精确信息,对模型不确定性和外部干扰具有鲁棒性。将该算法应用于卫星姿态控制系统,并与广义增量模型预测控制(GIPC)算法进行了比较。结果表明,该方法比GIPC方法具有更强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust model predictive control based on MRAS for satellite attitude control system
In this paper, a robust model predictive control (RMPC) is proposed based on model reference adaptive system (MRAS). In this algorithm, using the MRAS a combinational RMPC controller for three degree freedom satellite is designed such that the effect of moment of inertia uncertainty and external disturbance is compensated on the stability and performance of closed loop system. Control law is a state feedback which its gain is obtained by solving a convex optimization problem subject to several linear matrix inequalities (LMIs). To avoid the actuators saturation a linear matrix inequality is incorporated as LMI in the mentioned optimization problem. The advantages of this algorithm are needless to exact information from system's model, robustness against model uncertainties and external disturbance. The proposed algorithm is implemented on the satellite attitude control system and the results of them are compared to generalized incremental model predictive control (GIPC) algorithm. The results show that the suggestive controller is more robust than the GIPC method.
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