Adaptive Optimization Control Based on Improved Genetic Algorithm and Fuzzy Neural Network

Abstract

Fuzzy neural network with its own characteristics, strong ability to learn and easy to fit the system, is widely used in in practice. This article firstly put forward to the general model based on improved genetic algorithm and fuzzy neural network. Secondly introduce the four layers fuzzy neural network model. As the general fuzzy neural network often use BP algorithm to study which has the deficiency of difficult to avoid local minimum and hard to find the global optimum, therefore, this article design the fuzzy neural network based on the improved genetic algorithm. According to change the coding method crossover operators and mutation operators, it improves the optimizing capacity. And then, gives FNN-IGA programming diagram. Finally, the inverted pendulum simulation experiments show the superiority of the optimal control model.