Model predictive trajectory tracking control and thrust allocation for autonomous vessels

Ali Haseltalab, Vittorio Garofano, Maurits van Pampus, Rudy R. Negenborn

Research output: Contribution to journalConference articleScientificpeer-review

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The maneuvering control of autonomous vessels has been under extensive investigations by academic and industrial communities since it is one of the primary steps towards enabling unmanned shipping. In this paper, a model predictive control (MPC) approach is presented for trajectory tracking control of vessels which takes into account the thrust allocation (TA) problem in the presence of rotatable thrusters. In this approach, the TA problem is formulated over a finite horizon and solved with regard to the power consumption, changes in the angle and speed of actuators, and the operating constraints. In the proposed control approach, several linearization techniques have been employed to enable the adoption of quadratic programming approaches for solving the MPC's and TA's optimization problems. The performance of the proposed approach is evaluated through several simulation experiments using a replica vessel model.

Original languageEnglish
Pages (from-to)14532-14538
Issue number2
Publication statusPublished - 2020
Event21st IFAC World Congress 2020 - Berlin, Germany
Duration: 12 Jul 202017 Jul 2020


  • Autonomous vessels
  • Feedback linearization
  • Maneuvering control
  • Model predictive control
  • Quadratic programming
  • Thrust allocation


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