Neural Network Control for an Electro-optical Tracking System

This paper presents a neural network control application for the Electro Optical Tracking System (EOTS). The most important goal of the EOTS is to capture an object on the ground fast and safely. Since the EOTS is subject to disturbance from outside as well as inside, tracking performance is degraded. To reduce the effect of disturbances, neural network is introduced in the control loop. The proposed neural network control is aimed to reject outer disturbances and compensate for internal nonlinearities and uncertainties effectively. Simulation studies of applying the proposed neural network are presented.