The design and application of neural network controller based on genetic algorithms

This paper combines the advantages of both neural networks and genetic algorithms, and proposes a back-propagation neural network algorithm based on improved genetic algorithms. Simulation experiment shows the method is valid. And we design a neural network controller based on the algorithm, which is applied to optimization control in the interval circulating gas making process. Our simulation results are satisfactory, and verify that the controller has strong robustness and high control accuracy, which has important significance in the study of intelligent control for industrial process.