Modeling & Simulation of a Hoisting System Driven by PMLSM Based on Neural Network

The hoisting system driven by PMLSM is different from the traditional hoisting model in construction and control mechanism.It's difficult to reflect the kinetic characteristics of the system accurately on the base of analytical model because of the influence of many factors,such as the ferrite core's disconnection,the asymmetry of three-phase winding and the big fluctuating of parameter in the course of work etc.In this paper a dynamic model of this system was constructed on the base of BP network。meanwhile it's mainly introduced about the network's leaming algorithm and the method of modeling,the gain of training data and selection of the network training parameter.Simulation result and experimental verification show that this model reflects the basic kinetic characteristics of the system more realistically than the analytical model.It has practical value in analyzing characteristics and control tactics of the system.