PID Control Based on BP Neural Network

A BP neural network is utilized to achieve PID parameter self-adjustment based on Jacobian values.,which depends on a RBF neural network identification with slow convergence or on sign function with low precision.To gain Jacobian values,an algorithm is proposed in which a sign function is used based on a RBF neural network identification on line as bigger error and a RBF neural network identification is used as minor error. Results indicate that the effectiveness of this controller with high precision and fast convergence is superior to the sign function algorithm.