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This paper introduces a Shrinking-Horizon Model Predictive Control (SHMPC) algorithm for autonomous helicopter landings on moving ship decks, focusing on runtime efficiency and guaranteed timing. The approach uses a simplified planning model of the helicopter dynamics combined with a touchdown controller to ensure landings within a pre-specified time window, even with disturbances. Simulation results demonstrate high landing precision and disturbance rejection in strong winds, with millisecond-range computation times.
Achieve robust autonomous helicopter landings on moving ship decks with guaranteed timing, even in strong winds, using a computationally efficient shrinking-horizon MPC approach.
We present a runtime efficient algorithm for autonomous helicopter landings on moving ship decks based on Shrinking-Horizon Model Predictive Control (SHMPC). First, a suitable planning model capturing the relevant aspects of the full nonlinear helicopter dynamics is derived. Next, we use the SHMPC together with a touchdown controller stage to ensure a pre-specified maneuver time and an associated landing time window despite the presence of disturbances. A high disturbance rejection performance is achieved by designing an ancillary controller with disturbance feedback. Thus, given a target position and time, a safe landing with suitable terminal conditions is be guaranteed if the initial optimization problem is feasible. The efficacy of our approach is shown in simulation where all maneuvers achieve a high landing precision in strong winds while satisfying timing and operational constraints with maximum computation times in the millisecond range.
