Self-loading Adjustment of a Top-mounted Gun Based on a Novel Neural Slide Mode Control

To solve the nonlinearities and enhance the performances of a gun control system(GCS),a novel neural slide mode control(NSMC)strategy was proposed and implemented on the elevation and decline control of a certain top-mounted GCS.A novel switch function was employed and its corresponding gain was dynamically adjusted by the RBF neural network.Taking advantage of this strategy,optimum control performances and suppression of the inherent chatter phenomenon can be well achieved.Both numerical simulations and experiments on a semi-physics simulation platform were conducted to investigate the control performance of the GCS.The results demonstrate that the proposed NSMC is of high robustness to the parameter perturbation and load disturbance of the GCS.The proposed NSMC can satisfy the requirements of gun adjustments,and the fast,smooth and accurate adjustments of the gun can be well achieved.