Laser pointing stabilization and control in the submicroradian regime with neural networks
Authors:
- 1 February 2001
- journal article
- conference paper
- Published by AIP Publishing in Review of Scientific Instruments
- Vol. 72 (2) , 1339-1342
Abstract
The possibility of controling the pointing stability of a slowly pulsed Ti:Sapphire laser system by lowpass filters and artificial neural networks (NN) is investigated by performing time series analysis and computer simulations on experimentally measured datasets. The simulations show that at pulse repetition rates of 20 Hz it is possible to use a feedforward algorithm to reduce the angular standard deviation from 0.7 to 0.3 μrad. The properties and advantages of NN methods such as automatic adaptation characteristics of a time series are discussed.Keywords
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