This paper presents an adaptive event-triggered control strategy for guaranteeing predefined tracking performance of uncertain nonlinear underactuated underwater vehicles (UUVs) in the three-dimensional space. Compared with the related results in the literature, the main contribution of this paper is to develop a nonlinear error transformation approach for ensuring predefined three-dimensional tracking performance under the underactuated property of 6-DOF UUVs and limited network resources. A nonlinear tracking error function is designed using a linear velocity rotation matrix and a time-varying performance function. An adaptive event-triggered control scheme using the nonlinear tracking error function and neural networks is constructed to ensure the practical stability of the closed-loop system with predefined three-dimensional tracking performance. In the proposed control scheme, auxiliary stabilizing signals are designed to resolve the underactuated problem of UUVs. Simulation results are presented to illustrate the effectiveness of the theoretical methodology.

A nonlinear-observer-based design methodology is proposed for an adaptive event-driven output-feedback tracking problem with guaranteed performance of uncertain underactuated underwater vehicles (UUVs) in six-degrees-of-freedom (6-DOF). A nonlinear observer using adaptive neural networks is presented to estimate the velocity information in the presence of unknown nonlinearities in the dynamics of 6-DOF UUVs where a state transformation approach using a time-varying scaling factor is introduced. Then, an output-feedback tracker using a nonlinear error function and estimated states is recursively designed to overcome the underactuated problem of the system dynamics and to guarantee preselected control performance in three-dimensional space. It is shown that the tracking error of the nonlinear-observer-based output-feedback control system exponentially converges a small neighbourhood around the zero. Efficiency of the resulting output-feedback strategy is verified through a simulation.