A Method for Identification of External Disturbing Influences on Electric Drives of a Large Radio Telescope

It is proposed to apply a neural network observer in the problems of identification of an external disturbance in the form of a wind load acting on the main mirror of a large radio telescope. The mathematical description of the wind moment is analyzed taking into account its fluctuating component, which has a nonlinear random character. A method of constructing the structure of recurrent neural networks based on models of a nonlinear autoregressive with exogenous inputs for identification of nonlinear static and dynamic control objects is described. In computer simulation, the RMS error for different training algorithms is compared to study their identification accuracy. Design, training, and testing of recurrent neural networks is carried out in the MATLAB/Simulink software environment.