Method of AC Servo System Based on Genetic Algorithm and Neural Network PID Control

Abstract

BP network model has become one of the important neural network model which is used in many fields, but it has some defects. From a mathematical perspective, it is a nonlinear optimization problem, which inevitably has the local minima problem; BP neural network learning algorithm has slow convergence rate, and the convergence speed and the initial weights of choice; network structure, namely the hidden layer nodes selection still has no theory, but according to the experience. Based on the BP algorithm local extreme values, considering the genetic algorithm, combining with BP algorithm, the BP neural network optimization is achieved. Neural network using genetic algorithm optimization mainly includes three aspects: the connection weights of evolution, evolutionary network structure, learning the rules of evolution.