Implementation of hydraulically driven barrel shooting control by utilizing artificial neural networks

Abstract

The success of the shooting of a moving vehicle can be achieved by providing barrel stabilization. In the meantime, it is necessary barrel angle must be positioned is instantaneously calculated accurately. In this paper, the required barrel elevation angle was calculated via artificial neural networks and the shooting success to a fixed target from a moving tank was investigated. For this purpose, a mathematical model of a tank, which has four degrees of freedom, with a barrel mounted on it has been utilized. The barrel is moved using an inverted slider mechanism. The system is driven hydraulically by considering the movement of the piston–cylinder pair in the inverted slider mechanism. The conventional PID control method has been preferred for angular position control of the barrel. Simulations have been performed with the MATLAB package program. System responses have been obtained graphically and the results have been presented in tabular form. It is seen that the pressure, flow, etc. obtained from the results overlap with the physical system. It is observed that the elevation angle of 10 degrees is captured and shot very well when the vehicle is stationary. In the moving state of the vehicle, the 10-degree elevation angle capture as well. In the moving case, there are tiny deviations in the target hit but these values can be considered to be reasonable levels. The deviation amount for the target 4 kilometers away is 16.28 meters.