Predictive control of radio telescope using multi-layer perceptron neural network

Radio telescope (RT) installations are highly valuable assets and during the period of their service life they need regular repair and maintenance to be carried out for delivering satisfactory performance and minimizing downtime. With the growing automation technologies, predictive control can prove to be a better approach than the traditionally applied visual inspection policy and linear models. In this paper, Irbene Radio telescope RT-16 disk rotation control motors are analysed. Retrieved data from the small DC motor is used for the predictive control approach. A Multilayer Perceptron (MLP) network approach is used for prediction of the indicator voltage output which affects the monitoring of the disk rotating angle.