Dynamic Response and Maneuvering Strategies of a Hybrid Autonomous Underwater Vehicle in Hovering

Abstract

The Odyssey IV autonomous underwater vehicle (AUV) is the next generation of un- manned subsurface robots from the MIT Sea Grant AUV Laboratory. The Odyssey IV AUV has a novel propulsion system, which includes a pair of azimuthing thrusters for maneuvering in surge and heave. An analytical model was developed to describe the complex nonlinear vehicle dynamics, and experiments were performed to refine this model. The fluid dynamics of unsteady azimuthing marine propulsors are largely unstudied, especially for small vehicles like the Odyssey IV AUV. Experiments sug- gest that thrust developed by an azimuthing propulsor is dependent on the azimuth angle rate of change, and can substantially affect vehicle dynamics. A simple model capturing the effects of azimuthing on the thruster dynamics is developed, and is shown to improve behavior of the model. The use of azimuthing thrusters presents interesting problems and opportunities in maneuvering and control. Nonlinear model predictive control (MPC) is a technique that consists of the real-time optimization of a nonlinear dynamic system model, with the ability to handle constraints and nonlinearities. In this work, several variations of simulated and experimental MPC-based controllers are investigated. The primary challenge in applying nonlinear MPC to the Odyssey IV is solving the time intensive trajectory optimization problem online. Simulations suggest that MPC is able to capitalize on its knowledge of the system, allowing more aggressive trajectories than a traditional PID controller

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2009
Accession Number
ADA528126

Entities

People

  • Lauren A. Cooney

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Autonomous Underwater Vehicles
  • Buoyancy
  • Control Systems
  • Dynamic Response
  • Engineering
  • Fluid Mechanics
  • Geometry
  • Kalman Filters
  • Mechanical Engineering
  • Model Predictive Control
  • Navigation
  • Nonlinear Dynamics
  • Physics Laboratories
  • Propulsion Systems
  • Simulations
  • Two Dimensional
  • Underwater Vehicles

Fields of Study

  • Physics

Readers

  • European Security and Defence Policy (ESDP).
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space
  • Space - Spacecraft Maneuvers