摘要
空间望远镜分块式主镜的面形是由其背后布置的若干致动器控制的,是一个复杂的控制系统。应用BP神经网络的方法建立了以致动器作用力作为输入、镜面形变的Zernike多项式拟合系数作为输出的镜面形变模型。利用镜面有限元分析的大量数据对该模型进行了离线训练,并在最小二乘法的基础上,设计了加入单纯形修正算法的主镜面形静态控制器。仿真结果表明,应用该控制器对空间望远镜进行在线控制,控制精度优于最小二乘控制法。
The segmented primary mirror of space-based telescope is controlled by a number of actuators to achieve a required surface shape.The back-propagation(BP)neural network is applied to modeling the primary mirror surface with inputs of actuator applied force and outputs of Zernike polynomial coefficient.By using primary mirror finite element analysis data,the model is trained offline.Based on a least squares approach,the surface static controller with a corrector designed by simplex method was built.The simulation results show the efficacy of this control approach for space-based telescope real-time control,and it is superior to a least squares approach.
出处
《光学技术》
CAS
CSCD
北大核心
2006年第z1期239-242,共4页
Optical Technique
关键词
分块式主镜
面形控制
有限元分析
BP神经网络
单纯形法
segmented primary mirror
surface control
finite element analysis
BP neural network
simplex method
