Research of fine tracking servo system for FSO terminal
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摘要: 为了提高空间光通信中的精跟踪伺服系统的跟踪精度,采用神经网络比例-积分-微分算法,解决精跟踪伺服系统设计中光斑抖动时变不确定性和压电陶瓷驱动中存在的迟滞、蠕变和位移非线性等不足。通过3层结构反向传播神经网络自学习方法,在线调整比例-积分-微分控制器的系数,控制压电陶瓷驱动精瞄偏转镜偏转,最终达到精跟踪伺服系统优化控制。进行了理论分析和实验验证,取得了室内精跟踪数据。结果表明,神经网络比例-积分-微分控制算法增强了伺服系统鲁棒性,并提高了伺服系统实时性;采用400Hz的CCD,精跟踪伺服系统对40Hz以下的抖动能有效抑制,基本能满足在空间光通信中跟踪带宽需要。
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关键词:
- 光通信 /
- 精跟踪 /
- 自适应神经网络比例-积分-微分控制器 /
- 压电陶瓷驱
Abstract: In order to improve tracking precision,and solve the control problem of uncertainty of beacon vibration,creep resistance and nonlinearity long lagging of fast steering mirror(FSM),the fine tracking servo system was designed based on the proportion-integral-differential(PID) like neural network algorithm in free spatial optic(FSO) communication.With three layers of back propagation(BP) neural networks,the weights of neural network and the parameters could be adjusted to reduce beacon vibration by means of the function of self-learning and adaptability in real time,finally the system was optimally controlled with the mirror drived by piezoelectric ceramic(PZT) actuator on line.Experimental results demonstrate that the system effectively restrains 40Hz and less than 40Hz facular trembles,and can satisfy the tracking bandwidth in free space optic communication.Furthermore,the robust performance and real time are improved in the fine tracking servo system. -
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