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Modeling, Simulation, and Maneuvering Control of a Generic Submarine

Gage MacLin, Maxwell Hammond, Venanzio Cichella, J. Ezequiel Martin

TL;DR

This paper develops a fast, disturbance-aware framework for submarine guidance by coupling a CFD-calibrated reduced-order model (ROM) with two outer-loop controllers: path following (PF) and trajectory tracking (TT). Each outer loop provides reference commands (depth, yaw, velocity) to a common inner-loop $ \mathcal{L}_1$ adaptive augmentor that enhances a fixed autopilot, enabling robust maneuvering under waves and near-surface effects. The authors derive stability proofs for both PF and TT via Lyapunov functions, and validate performance on a Joubert BB2 ROM using bathymetric scenarios and near-surface disturbances, with detailed CFD-based coefficient generation and a public Simulink model. The results show that both PF and TT can achieve complex maneuvers, with PF offering velocity flexibility and TT ensuring a prescribed finish time, while the adaptive inner loop improves disturbance rejection and convergence speed. Overall, the work enables rapid development and testing of submarine control algorithms in challenging aquatic environments, bridging high-fidelity CFD data with practical autopilot augmentation.

Abstract

This work introduces two multi-level control strategies to address the problem of guidance and control of underwater vehicles. An outer-loop path-following algorithm and an outer-loop trajectory tracking algorithm are presented. Both outer-loop algorithms provide reference commands that enable the generic submarine to adhere to a three-dimensional path, and both use an inner-loop adaptive controller to determine the required actuation commands. Further, a reduced order model of a generic submarine is presented. Computational fluid dynamics (CFD) results are used to create and validate a model that includes depth dependence and the effect of waves on the craft. %The model and the procedure to obtain its coefficients are discussed, and examples of the data used to obtain the model coefficients are presented. An example of operation following a complex path is presented and Results from the reduced order model for each control strategy are compared.

Modeling, Simulation, and Maneuvering Control of a Generic Submarine

TL;DR

This paper develops a fast, disturbance-aware framework for submarine guidance by coupling a CFD-calibrated reduced-order model (ROM) with two outer-loop controllers: path following (PF) and trajectory tracking (TT). Each outer loop provides reference commands (depth, yaw, velocity) to a common inner-loop adaptive augmentor that enhances a fixed autopilot, enabling robust maneuvering under waves and near-surface effects. The authors derive stability proofs for both PF and TT via Lyapunov functions, and validate performance on a Joubert BB2 ROM using bathymetric scenarios and near-surface disturbances, with detailed CFD-based coefficient generation and a public Simulink model. The results show that both PF and TT can achieve complex maneuvers, with PF offering velocity flexibility and TT ensuring a prescribed finish time, while the adaptive inner loop improves disturbance rejection and convergence speed. Overall, the work enables rapid development and testing of submarine control algorithms in challenging aquatic environments, bridging high-fidelity CFD data with practical autopilot augmentation.

Abstract

This work introduces two multi-level control strategies to address the problem of guidance and control of underwater vehicles. An outer-loop path-following algorithm and an outer-loop trajectory tracking algorithm are presented. Both outer-loop algorithms provide reference commands that enable the generic submarine to adhere to a three-dimensional path, and both use an inner-loop adaptive controller to determine the required actuation commands. Further, a reduced order model of a generic submarine is presented. Computational fluid dynamics (CFD) results are used to create and validate a model that includes depth dependence and the effect of waves on the craft. %The model and the procedure to obtain its coefficients are discussed, and examples of the data used to obtain the model coefficients are presented. An example of operation following a complex path is presented and Results from the reduced order model for each control strategy are compared.
Paper Structure (16 sections, 2 theorems, 38 equations, 14 figures, 1 table)

This paper contains 16 sections, 2 theorems, 38 equations, 14 figures, 1 table.

Table of Contents

  1. Introduction
  2. Modeling
  3. Joubert BB2
  4. Hydrodynamic Model
  5. Computational Fluid Dynamics
  6. Control
  7. Path Following
  8. Trajectory Tracking
  9. Adaptive Inner-Loop Control
  10. Results
  11. Adaptation
  12. Path-Following and Trajectory Tracking Bathymetry Example
  13. Summary and Conclusions
  14. Appendix
  15. Path-Following Lyapunov Proof
  16. ...and 1 more sections

Key Result

Theorem 1

Consider a vehicle equipped with an inner-loop autopilot that satisfies Equation asm:AP. There exist control parameters $d$ and $k_\gamma$ such that, for any initial state $p_T(0)$ the rate of progression of the virtual time eq:gammad and the orientation command eq:pfrot ensure that the path-followi

Figures (14)

  • Figure 1: Definition of axes and variables used for modelling BB2.
  • Figure 2: Triangulated surface for hydrostatic load calculation. The total number of elements $N_e$ is 7,148.
  • Figure 3: The overall control structure highlighting the path-following controller and the adaptive augmentation algorithm
  • Figure 4: The overall control structure highlighting the trajectory tracking controller and the adaptive augmentation algorithm
  • Figure 5: Geometry associated with the path-following and trajectory tracking problems
  • ...and 9 more figures

Theorems & Definitions (4)

  • Theorem 1
  • Proof 1
  • Theorem 2
  • Proof 2