Application of NN-based backstepping adaptive controller for stabilized platform of shipborne weapons

A neural network (NN)-based backstepping adaptive control is proposed for the stabilized platform system of shipborne weapons (SPOSW) with uncertain nonlinear friction torque and load disturbance. First, with the using of NN approximator, an equivalent model is developed. Where the NN is used to estimate the uncertain nonlinear friction torque. Then, based on the equivalent model, address the problem of reconstruction error and disturbance load, an adaptive backstepping control scheme is proposed for the stabilized platform system. Moreover, the analysis of stability can be completed by Lyapunov stability theory, and the convergence rate of the tracking error can be governed by the choice of the control parameter values. Finally, to demonstrate the effectiveness of the proposed control scheme, simulation results are illustrated.