An Experimental Study on Sensorless Determination of the Projectile Position by Artificial Neural Network in Magnetic Launcher Systems

Abstract

Electromagnetic launchers are systems in which energy is converted from one form to another. The energy applied to the launcher is converted into magnetic energy in the coil and then into motion energy. The object to be launched follows the magnetic field created in one or more fixed coils. The coil can be fed by direct current (dc) or alternative current (ac) source. In dc systems, the capacitor charging time delays the serial launch. In ac systems, the absence of capacitors enables serial launching. In this study, the application of an ac electromagnetic launch system, which provides a serial launch, is proposed. The maximum force acting on the projectile can be achieved by timely cutting off the energy applied to the coil. Therefore, in electromagnetic launchers, it is critical to know the position of the projectile in the coil. In launcher systems fed with alternating current, the projectile position can be predicted from current changes without the need for an additional setup. In the study, TMS320F28335 digital signal processor (DSP) microprocessor with high processing capacity was used to detect the trigger moment from coil current. Time-delayed artificial neural network was used to estimate the position of the projectile within the coil by using the obtained current differences. The normalized values of the current differences were applied to the time-delayed multilayer neural network (MLNN) algorithm and the projectile position was estimated with 94.67% accuracy. The proposed system increases efficiency compared to systems using conventional sensors, as it prevents or reduces the retraction force.