Multi-Trajectory Planning Control Strategy for Hydropower Plant Bridge Crane Based on Evaluation Algorithm

Currently, the research on crane trajectory planning mostly aims to, first, plan the trajectories of the crane and the trolley, and then to use a trial-and-error method or optimization algorithm to iteratively calculate the optimal trajectory parameters under the control of the optimal trajectory parameters to achieve the suppression of the swing angle. However, research on the fusion application of multi-trajectory planning algorithms is very rare. In addition, the existing methods are not suitable for the special operation control of hydropower plant bridge cranes. Based on the application scenario of hydropower plant bridge cranes, this paper proposes a comprehensive multi-trajectory control strategy based on the entropy weight technique for order preference, similarly to the ideal solution (TOPSIS) evaluation method. Specifically, the kinematic analysis of the crane is carried out and the trajectory evaluation index system is established. Secondly, under the walking constraint condition, four different trajectory planning algorithms are used to obtain the crane trajectory curve. In order to ensure the accuracy and comprehensiveness of the evaluation, the evaluation data are obtained through the Adams motion simulation platform. Finally, based on the entropy weight TOPSIS evaluation method, the optimal walking trajectory for each displacement is selected. The simulation and experimental results show that the evaluation method can select the optimal trajectory based on the motion characteristics of the trajectory algorithm in different displacement conditions, effectively reducing the load swing during the walking process of the crane and improving the positioning accuracy.