The Application Research of Ant Colony Optimization Algorithm for Intelligent Control on Special Crane

The special crane studied in this paper is a combination of industrial arm and crane system worked on the ship. For this system, a dynamic model was built and a kind of intelligent control method based on fuzzy neural network optimized and trained by the ant colony optimization algorithm (ACOA) was proposed in the paper. The structure and the parameters of this intelligent controller are designed and presented. This intelligent control method is used as articular servo controller to apply in the simulation research of special crane control. By comparison that has been carried out to evaluate the performance between proposed ACOA method and back propagation algorithm, the simulation results showed that the trajectory tracking effect and the precision of mechanical arm control of this special carne can be improved and have good quick convergence performance for training based on ACOA. This intelligent control method has a good application prospects in other correlative fields.