Adaptive backstepping and sliding mode control of fin stabilizer based on RBF neural network

Considering the influence of uncertainty as unknown nonlinearity, parameters perturbation and random waves disturbance to the fin stabilizer system during ship sailing in heavy sea, the random wave model is built and a robust controller based on adaptive backstepping, sliding mode and RBF neural network is proposed. Adaptive backstepping and sliding mode control is the main controller and RBF neural network is used to compute the upper bound value of uncertainty which is composed of unknown nonlinearity, parameters perturbation and random waves disturbance, then the system stability is analyzed by using the Lyapunov theory. The simulation results show that the control strategy is effective to decrease roll motion of fin stabilizer system in different sea conditions and has strong robust stability to overcome the uncertainty.