Nonlinear-Observer-Based Design Approach for Adaptive Event-Driven Tracking of Uncertain Underactuated Underwater Vehicles

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.

Automated summary

This methodology proposes a nonlinear-observer-based design approach with adaptive neural networks for tracking underactuated underwater vehicles (UUVs), ensuring performance while estimating velocity information in the presence of unknown nonlinearities. By introducing a time-varying scaling factor, a state transformation technique is employed to effectively estimate the velocity information.