Flatness-based Model Predictive Payload Control for Offshore Cranes

Crane-based cargo handling at sea is subject to a variety of disturbances linked to the sea swell. During rough sea states, spatial payload oscillations occur, which render safe loading operations challenging. Therefore, increasing effort is made to automate disturbance rejection in terms of sway reduction (Anti Sway Control) and vertical position control (Active Heave Compensation). In this context, model predictive control (MPC) has been studied, which allows to consider both stabilization and tracking problems. In context of this contribution, a predictive controller based on the differential flatness of the crane system is presented, which facilitates real-time control while attaining a high damping performance with respect to the swinging payload. The controller design is evaluated in simulation for varying sea disturbances. The results suggest good tracking capabilities, where the payload’s position error is reduced up to 85% for light to medium sea states. In comparison to a nonlinear formulation of the MPC problem, computational complexity is furthermore reduced, enabling fast sample times around 10 ms.