Performance-maximum optimization of the intelligent lifting activities for a polar ship crane through trajectory planning

Knuckle boom crane (KBC) mounted on a polar ship (PS) is a maritime engineering equipment widely used in offshore activities. The working performance of a PS-mounted KBC (PSKBC) may degrade quickly if manipulated manually under extreme working conditions in polar region. To address the challenges, a performance-maximum optimization method through trajectory planning is developed to further promote the intelligently unmanned lifting processes of the PSKBC. Firstly, the dynamic model of lifting activities of the PSKBC is established using Lagrangian equation, based on which the point-to-point trajectory planning (PTP) method is developed for lifting processes. Subsequently, the PTP-based optimization model is established to realize the minimum energy consumption and time cost of the lifting activities of the PSKBC, and the obtained optimal lifting performance is compared with the traditional S-curve method. To verify the superiority of the proposed performance-maximum optimization method, numerical simulations of the lifting activities of the PSKBC with respect to different crane loads and final lifting positions are performed. Results indicate that the PTP-based performance-maximum optimization method for the PSKBC can perfectly achieve better performances with applicable lifting trajectories regarding various working conditions and demands.