Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Guidance and Control of Unmanned Surface Vehicles via HEOL

Loïck Degorre, Emmanuel Delaleau, Cédric Join, Michel Fliess

TL;DR

HEOL addresses robust trajectory tracking for USVs by integrating flatness-based guidance with model-free adaptive control via iPD. It leverages a flat hovercraft nominal model to derive a guidance law and uses iPD to compensate disturbances and modeling errors, with a heading inner loop for cascade stability. Simulation results on a hovercraft and a USV show rapid error convergence under wind-like disturbances, validating robustness to model mismatch. The approach offers a practical, adaptable framework for all-purpose marine craft control with potential extensions to underwater vehicles.

Abstract

This work presents a new approach to the guidance and control of marine craft via HEOL, i.e., a new way of combining flatness-based and model-free controllers. Its goal is to develop a general regulator for Unmanned Surface Vehicles (USV). To do so, the well-known USV maneuvering model is simplified into a nominal Hovercraft model which is flat. A flatness-based controller is derived for the simplified USV model and the loop is closed via an intelligent proportional-derivative (iPD) regulator. We thus associate the well-documented natural robustness of flatness-based control and adaptivity of iPDs. The controller is applied in simulation to two surface vessels, one meeting the simplifying hypotheses, the other one being a generic USV of the literature. It is shown to stabilize both systems even in the presence of unmodeled environmental disturbances.

Guidance and Control of Unmanned Surface Vehicles via HEOL

TL;DR

HEOL addresses robust trajectory tracking for USVs by integrating flatness-based guidance with model-free adaptive control via iPD. It leverages a flat hovercraft nominal model to derive a guidance law and uses iPD to compensate disturbances and modeling errors, with a heading inner loop for cascade stability. Simulation results on a hovercraft and a USV show rapid error convergence under wind-like disturbances, validating robustness to model mismatch. The approach offers a practical, adaptable framework for all-purpose marine craft control with potential extensions to underwater vehicles.

Abstract

This work presents a new approach to the guidance and control of marine craft via HEOL, i.e., a new way of combining flatness-based and model-free controllers. Its goal is to develop a general regulator for Unmanned Surface Vehicles (USV). To do so, the well-known USV maneuvering model is simplified into a nominal Hovercraft model which is flat. A flatness-based controller is derived for the simplified USV model and the loop is closed via an intelligent proportional-derivative (iPD) regulator. We thus associate the well-documented natural robustness of flatness-based control and adaptivity of iPDs. The controller is applied in simulation to two surface vessels, one meeting the simplifying hypotheses, the other one being a generic USV of the literature. It is shown to stabilize both systems even in the presence of unmodeled environmental disturbances.
Paper Structure (15 sections, 20 equations, 8 figures)

This paper contains 15 sections, 20 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Model of the Vehicle
  3. Surface vessel model
  4. Hovercraft model
  5. Flatness of the hovercraft model
  6. Preliminary remark
  7. Proof
  8. Brunovský representation
  9. Design of the controller
  10. Nominal Controls
  11. Closed-loop control design
  12. Simulation Results
  13. Control of the hovercraft
  14. Control of a standard USV
  15. Conclusion

Figures (8)

  • Figure 1: Schematic representation of the hovercraft.
  • Figure 2: Cascade structure
  • Figure 3: Trajectory of the hovercraft in the $(\mathbold{x_0}, \mathbold{y_0}$) plane, in presence of a wind force aligned with the $\mathbold{y_0}$ axis. Black: Reference trajectory - Blue: Actual trajectory of the vehicle
  • Figure 4: Tracking errors of the hovercraft over time. Blue: Error on the $\mathbold{x_0}$ axis - Orange: Error on the $\mathbold{y_0}$ axis
  • Figure 5: Estimated values of $F_x$ and $F_y$ over time for the hovercraft. Dashed Black: Wind force - Blue: $\widehat{F}_x$ - Orange:$\widehat{F}_y$
  • ...and 3 more figures

Theorems & Definitions (2)

  • Remark 1
  • Remark 2