摘要
为克服摩擦对卫星光通信(IOC)瞄准捕获跟踪(PAT)粗瞄子系统的精度控制的影响,首先利用PD控制器以获得稳定的轨迹;再用一种扩展的神经网络结构在线逼近摩擦函数,对摩擦力矩进行补偿;在此基础上,利用传统单层神经网络和自适应的鲁棒项消除神经网络的逼近误差及外部扰动。最后用李亚普诺夫函数方法证明在本文的控制策略下,可以保证系统的渐近稳定性和参数的有界性。
In order to compensate for the effects of friction in IOC （Inter-satellite Optical Communication） coarse pointing subsystem of PAT（Pointing, Acquisition, Tracking） system,a PD controller is used to obtain a stable trajectory first, then an augmented neural network is used to approximate the friction function on line to compensate for it. In addition, the traditional neural network and adaptive robust terms are used to eliminate the effects of approximation error of neural network and external disturbances. At last, the system is proved to be asymptotically stable and the parameters are proved to be bounded under the control scheme of this paper, using Lyapunov function methods.
出处
《航空学报》
EI
CAS
CSCD
北大核心
2007年第2期358-364,共7页
Acta Aeronautica et Astronautica Sinica
基金
哈尔滨工业大学校基金(HIT2002121)
关键词
卫星光通信(IOC)
瞄准
捕获
跟踪(PAT)
摩擦补偿
神经网络
自适应鲁棒项
inter-satellite optical communication （IOC）
pointing, acquisition, tracking （PAT）
friction compensation
neural network
adaptive robust term
