A Crane Overload Protection Controller for Blade Lifting Operation Based on Model Predictive Control

Abstract

Lifting is a frequently used offshore operation. In this paper, a nonlinear model predictive control (NMPC) scheme is proposed to overcome the sudden peak tension and snap loads in the lifting wires caused by lifting speed changes in a wind turbine blade lifting operation. The objectives are to improve installation efficiency and ensure operational safety. A simplified three-dimensional crane-wire-blade model is adopted to design the optimal control algorithm. A crane winch servo motor is controlled by the NMPC controller. The direct multiple shooting approach is applied to solve the nonlinear programming problem. High-fidelity simulations of the lifting operations are implemented based on a turbulent wind field with the MarIn and CaSADi toolkit in MATLAB. By well-tuned weighting matrices, the NMPC controller is capable of preventing snap loads and axial peak tension, while ensuring efficient lifting operation. The performance is verified through a sensitivity study, compared with a typical PD controller.