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

• Main Authors: Jin Hoe Kim, Sung Jin Yoo
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Mathematics
• Subjects: adaptive neural network observer; event-driven three-dimensional tracking; output-feedback; guaranteed performance; underactuated underwater vehicles (UUVs)
• Online Access: https://www.mdpi.com/2227-7390/9/10/1144

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.