Variable curvature bending arc control method for roll bending machine

Abstract

A variable curvature bending arc control method for a roll bending machine includes specific steps as follows: collecting and pre-processing data; initializing the network structure, and determining the parameters such as a number of input layer nodes, hidden layer nodes and output layer nodes and other parameters of the back propagation neural network according to the learning sample data; encoding a weight value and a threshold value of a back propagation neural network into individuals in a population according to set coding rules, and initializing the population according to a set population size and a random initialization method; GA-PSO iterative operation; initializing the back propagation neural network parameter; training the back propagation neural network; and an application of the control model. The control method accurately controls the variable curvature bending arc torque for the roll bending machine by combining genetic algorithm, back propagation neural network and particle swarm optimization.