Improved Neural Network Based on Genetic Algorithm in the Application for Tuning of PI Controllers

To overcome the disadvantage of conventional neutral network which is training only offline, an improved neutral network based on genetic algorithm is proposed. Starting from the performance index of self-tuning PI controllers, principle of recurrent neutral network and speed control system model of induction motor are elaborated. Then, the feasibility of by genetic algorithm to seak optimal constants of extended kalman filter is explained. Finally, modeling and simulation are performed by MATLAB/Simulink with control system of induction motors as platform. The results show that the PI parameters obtained by the proposed improved neutral network based on genetic algorithm can reduce the overshoot of system effectively and the system has good dynamic and static performance.