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基于气动力矩和模型预测的LEO卫星角动量管理算法
引用本文:张学钢,朱振才,陈宏宇.基于气动力矩和模型预测的LEO卫星角动量管理算法[J].控制与决策,2019,34(11):2452-2458.
作者姓名:张学钢  朱振才  陈宏宇
作者单位:中国科学院微小卫星创新研究院,上海201203;中国科学院上海微系统与信息技术研究所,上海200050;中国科学院大学,北京100049;中国科学院微小卫星创新研究院,上海201203;上海科技大学信息科学与技术学院,上海201210
摘    要:为抑制气动力矩对近地轨道(LEO)卫星姿态控制系统的影响,改善卫星电磁环境,设计一种基于气动力矩和模型预测的LEO卫星角动量管理算法,利用气动力矩管理卫星角动量并通过磁力矩器辅助提高角动量管理效率和可靠性.利用所设计的角动量管理算法构建卫星姿态动力学的线性化模型和姿态控制律,预测角动量变化趋势;通过在卫星太阳阵常规运动上附加额外的小角度偏转,将LEO卫星主导摄动力矩的气动力矩转化为管理卫星角动量的控制力矩.仿真实验表明,与传统的角动量管理策略相比,所设计的角动量管理算法通过将气动力矩转化为角动量管理控制力矩,能够有效节省卫星角动量管理的消耗.此外,该算法在不增加物理机构的前提下可以作为卫星的备用角动量管理策略,能够显著增强卫星姿态系统的可靠性和鲁棒性.

关 键 词:气动力矩  模型预测  二次规划间题  角动量管理  太阳阵

LEO satellites momentum management based on predictive model and aerodynamic torque
ZHANG Xue-gang,ZHU Zhen-cai and CHEN Hong-yu.LEO satellites momentum management based on predictive model and aerodynamic torque[J].Control and Decision,2019,34(11):2452-2458.
Authors:ZHANG Xue-gang  ZHU Zhen-cai and CHEN Hong-yu
Affiliation:Innovation Academy for Microsatellites,Chinese Academy of Sciences,Shanghai201203,China;Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences,Shanghai200050,China;University of Chinese Academy of Sciences,Beijng100049,China,Innovation Academy for Microsatellites,Chinese Academy of Sciences,Shanghai201203,China;School of Information Science and Technology,ShanghaiTech University,Shanghai201210,China and Innovation Academy for Microsatellites,Chinese Academy of Sciences,Shanghai201203,China;School of Information Science and Technology,ShanghaiTech University,Shanghai201210,China
Abstract:To depress the influence on satellite attitude control caused by environment torque, decrease the propellant consumption, and improve the electromagnetic environment in satellites, a momentum management algorithm is proposed for low earth orbit(LEO) satellites, which utilizes moment wheels to control attitude and aerodynamic torque to manage momentum. The proposed algorithm predicts the momentum variation via the linearized attitude dynamic model and corresponding control law, manages momentum utilizing the dominant aerodynamic torque through controlling the tiny rotation angle of the solar array, and adopts quadratic programming algorithm to optimize the management result. Compared with traditional schemes, simulations with high-fidelity space environment models demonstrate the proposed algorithm has ability to reduce energy consumption via converting the dominant environment perturbation into control torque. Besides, the proposed algorithm can enhance the reliability and robustness of the system by being treated as redundant momentum management strategy without any extra physical devices.
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