含模型不确定性和状态约束的航天器姿态鲁棒控制  

Robust Attitude Control for Spacecraft with Model Uncertainty and State Constraints

作　　者：林晓冬 张锐 LIN Xiaodong;ZHANG Rui(Innovation Academy for Microsatellites of CAS,Shanghai 201203,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院微小卫星创新研究院,上海201203 [2]中国科学院大学,北京100049

出　　处：《宇航学报》2022年第6期781-789,共9页Journal of Astronautics

摘　　要：针对严格反馈三轴稳定航天器姿态控制问题,在考虑航天器系统存在模型不确定性、未知外部扰动、系统存在时延情况下,提出了一种鲁棒控制方法。首先建立航天器误差运动学和动力学模型,使用神经网络对系统不确定性和未知扰动进行逼近、引入障碍李雅普诺夫函数对系统状态约束进行处理;然后利用反步法构造一种鲁棒自适应姿态控制器,通过李雅普诺夫方法证明闭环系统是最终一致有界的;最后,结合工程实际经验对系统已知时延进行前馈补偿。半物理仿真结果表明了所设计控制器的有效性和鲁棒性。Aiming at the attitude control problems of strict-feedback three-axis stabilized spacecraft,a robust control method is proposed considering the existence of model uncertainty,unknown external disturbance and system delay.Firstly,the kinematics and dynamics models of spacecraft errors are established.The neural network is used to approximate the uncertainty and unknown disturbance of the system,and the barrier Lyapunov function is introduced to deal with the system state constraints.Then,a robust adaptive attitude controller is constructed by backstepping method,and the closed-loop system is proved to be uniformly bounded by the Lyapunov method.Finally,the feedforward compensation for the known time delay is carried out based on practical engineering experience.The semi-physical simulation results show the effectiveness and robustness of the proposed controller.

关 键 词：反步法 障碍李雅普诺夫函数 自适应神经网络 半物理仿真 

分 类 号：V448.2[航空宇航科学与技术—飞行器设计]