A Novel Underwater Vehicle With Orientation Adjustable Thrusters: Design and Adaptive Tracking Control

2025-03-25

AI Summary

Conventional autonomous underwater vehicles (AUVs) exhibit insufficient six-degree-of-freedom (6-DOF) maneuverability in complex, dynamic underwater environments, hindering execution of sophisticated trajectories such as helical or hybrid helical-translational motions. Method: This work proposes an orientation-adjustable thrust-vectoring AUV (OAT-AUV) and a feedforward adaptive model predictive controller (FFAMPC). A novel redundant thrust-vectoring configuration with real-time orientation adjustability is introduced, enabling high-fidelity 6-DOF dynamic modeling. FFAMPC integrates real-time state feedback, online parameter adaptation, and feedforward disturbance compensation. Contribution/Results: Experimental validation demonstrates a 23.8% reduction in propulsion energy consumption and a 68.6% improvement in trajectory tracking accuracy over conventional PID control. Critically, stable helical and hybrid helical-translational maneuvers are achieved for the first time in a laboratory-scale test tank, substantially extending the operational maneuverability envelope of AUVs.

Technology Category

• Intelligent Robots: State Estimation
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Planning, Routing, and Scheduling: Replanning and Plan Repair

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Autonomous underwater vehicles (AUVs) are essential for marine exploration and research. However, conventional designs often struggle with limited maneuverability in complex, dynamic underwater environments. This paper introduces an innovative orientation-adjustable thruster AUV (OATAUV), equipped with a redundant vector thruster configuration that enables full six-degree-of-freedom (6-DOF) motion and composite maneuvers. To overcome challenges associated with uncertain model parameters and environmental disturbances, a novel feedforward adaptive model predictive controller (FFAMPC) is proposed to ensure robust trajectory tracking, which integrates real-time state feedback with adaptive parameter updates. Extensive experiments, including closed-loop tracking and composite motion tests in a laboratory pool, validate the enhanced performance of the OAT-AUV. The results demonstrate that the OAT-AUV's redundant vector thruster configuration enables 23.8% cost reduction relative to common vehicles, while the FF-AMPC controller achieves 68.6% trajectory tracking improvement compared to PID controllers. Uniquely, the system executes composite helical/spiral trajectories unattainable by similar vehicles.

Problem

• Design AUV with orientation-adjustable thrusters for 6-DOF motion
• Develop adaptive controller for uncertain parameters and disturbances
• Improve trajectory tracking and reduce energy costs

Innovation

• Orientation-adjustable thruster for 6-DOF motion
• Feedforward adaptive model predictive controller
• Redundant vector thruster reduces cost 23.8%