Laser pointing stabilization and control in the submicroradian regime withneural networks

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 simulatio ns 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 mu rad. The propertie s and advantages of NN methods such as automatic adaptation characteristics of a time series are discussed. (C) 2001 American Institute of Physics.