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March 4, 2026at - Automatisierungstechnik0 citations

Recent advances in tracking control of hydrobatic AUVs

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TSTom Vincent SlawikLCLeif ChristensenFKFrank Kirchner

Key Points

  • The aim is to overview recent advancements in control strategies for hydrobatic AUVs that enhance maneuverability and precision.
  • Reviewed various control systems applicable to hydrobatic AUVs.
  • Discussed Nonlinear Model Predictive Control (NMPC) for its robustness and timing guarantees.
  • Explored classical control strategies like Sliding Mode Control (SMC) and Backstepping.
  • Identified NMPC as effective for managing nonlinear models with constraints.
  • Showed classical methods remain valuable due to their lower computational requirements.
  • Highlighted the importance of timing-aware control in ensuring effective maneuvering under uncertainties.

Abstract

Abstract The term hydrobatics is inspired by aerobatics and refers to a new class of highly dynamic maneuvers performed by Autonomous Underwater Vehicles (AUVs) with maximum agility and precision. Due to the complex interaction with the ocean environment, advanced control systems are required, which allow for precise maneuvering despite model uncertainties and external disturbances such as ocean currents. In addition, time-critical maneuvers often demand formal timing guarantees, such as fixed-time or finite-time convergence. Nonlinear Model Predictive Control (NMPC) is one of the dominant approaches for tracking control, due to its ability to handle nonlinear models and its constraint satisfaction guarantees. However, classical control strategies - including Sliding Mode Control (SMC), Backstepping, and Incremental Nonlinear Dynamic Inversion (INDI) also remain relevant, due to their robustness to model uncertainties and lower computational demands. This work provides an overview of the recent advances in control strategies for hydrobatic AUVs, with a focus on robustness, performance guarantees, and timing-aware control design.

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Cite This Study

Slawik et al. (2026) studied this question.

synapsesocial.com/papers/69a7cd0bd48f933b5eed8f9ahttps://doi.org/10.1515/auto-2025-0071
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