Finite-Time Sliding Mode Control for Undersea Vehicles

Abstract

A finite-time sliding mode control system based on a radial basis function (RBF) neural network was proposed to solve the longitudinal control problem of incomplete submerged vehicles because of the uncertainty and nonlinearity of undersea vehicle systems. The unknown term in the state space equation of undersea vehicles was compensated for by the estimated value of the neural network, and the weight of the neural network was updated by the corresponding adaptive law. The stability of the system was proved by Lyapunov stability theory, where the tracking error could converge to a small neighborhood near zero within a finite time. The simulation results show that the control system proposed in this paper can make the undersea vehicle track the desired trajectory within a finite time.

Keywords

• undersea vehicle
• finite-time control
• sliding mode control
• radial basis function