Adaptive fuzzy nonlinear integral sliding mode control for unmanned underwater vehicles based on ESO

Abstract

An adaptive fuzzy nonlinear integral sliding mode control strategy based on an extended state observer (ESO) is proposed for trajectory tracking of unmanned underwater vehicles (UUVs) in the presence of unknown external disturbances and model parameter uncertainties. A nonlinear dynamics error model of the UUV is established; the estimation of the lumped disturbances are estimated using ESO, and the control variables are compensated for in real time. A nonlinear integral sliding mode controller with saturation characteristics is designed to improve the transient and steady-state performance of the system, and the switching gain of the sliding mode control is adaptively adjusted using the fuzzy logic system, such that the weight of the output changes with the sliding mode surface; thus, the chattering of the control variables is weakened. The asymptotic stability of the control system is verified using Lyapunov stability theory. The simulation and experimental results demonstrated that the designed control strategy effectively suppresses the system lumped disturbances with high tracking accuracy and robustness.