Hierarchical inversion-based output tracking control for uncertain autonomous underwater vehicles using extended Kalman filter

Hsiu Ming Wu, Mansour Karkoub

Research output: Contribution to journalArticle


In this study, a hierarchical inversion-based output tracking controller (HIOTC) is developed for an autonomous underwater vehicle (AUV) subject to random uncertainties (e.g., current disturbances, unmodeled dynamics, and parameter variations) and noises (e.g., process and measurement noises). The proposed HIOTC respectively utilizes a combination of feedforward and feedback controls in a hierarchical structure based on the kinematic and dynamic models of the system. Moreover, to obtain uncontaminated or unavailable states for implementing the proposed control law, the extended Kalman filter (EKF) is employed to estimate the system states. Then, the position outputs, orientation, and velocity of the AUV are reached with guaranteed asymptotic stability. The robustness of the proposed HIOTC is verified through injection of random uncertainties into the system model. The closed-loop stability of the proposed individual subsystems is respectively guaranteed to have uniformly ultimately bounded (UUB) performance based on the Lyapunov stability criteria. In addition, the asymptotic tracking of the overall system is demonstrated using Barbalat's lemma. Finally, the feasibility and effectiveness of the proposed control scheme are evaluated through computer simulations and it is shown that the overall system achieves good asymptotic tracking performance.

Original languageEnglish
JournalAsian Journal of Control
Publication statusAccepted/In press - 1 Jan 2019



  • autonomous underwater vehicle
  • Barbalat's lemma
  • extended Kalman filter
  • hierarchical inversion-based output tracking controller
  • Lyapunov stability criteria

ASJC Scopus subject areas

  • Control and Systems Engineering

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