Flatness Control based on Improved Genetic Algorithm to Optimize the Neural Network
The system of automatic flatness control is a multi-input and multi-output nonlinear system with strong coupling,therefore,it is difficult to build an accurate mathematical model,the control method of general routine is difficult to obtain satisfactory control effect.Based on the local rolling data,this thesis puts forward a method of using neural network which is optimized by adaptive competition genetic algorithm for modeling the cold rolling,then using fuzzy control realize the real-time control,the simulation results of MATLAB programming show the effectiveness and timeliness of the algorithm.