Neuroadaptive Sliding Mode Formation Control of Autonomous Underwater Vehicles With Uncertain Dynamics

Abstract

This article investigates the leader–follower formation control problem for the multiple underactuated autonomous underwater vehicles with model uncertainties and external disturbances. Sliding mode control, multilayer neural network, and adaptive robust techniques are employed to design a formation controller for underwater vehicles. After that, a Lyapunov-based stability analysis is proposed to guarantee that all variables are uniformly ultimately bounded in the closed-loop control system. The following advantages of this approach are highlighted: 1) the proposed control strategy only depends on the measurements of line-of-sight and angle sensors; no other information about the leader vehicle is required; 2) a continuous function is designed to replace the signum term in the control system, which greatly reduces the inherent chattering of sliding mode controller; 3) the proposed controller does not rely on any prior knowledge about hydrodynamic damping and external disturbances, which is easily implemented in practice. Finally, the numerical simulations are provided to demonstrate the effectiveness of the proposed controller.