Design of PID excitation controllers for synchronous generators based on fuzzy RBF neural network

A new kind of excitation control scheme in which the fuzzy control and neural network technique is integrated to the design of the generator nonlinear control is proposed. Based on the theory of the synchronous generator excitation control system, one machine-infinity power system nonlinear mathematical model expressed by state equation is established. A fuzzy RBF (Radial Basis Function) neural network is constructed. An implementation of on-line automatic adjustment of the PID excitation regulator parameters is done according to the fuzzy RBF neural network control decision-making. A great number of simulation tests are made and a comparison with the conventional PID excitation control is performed. The simulation results show that the excitation control system based on the fuzzy RBF neural network has the excellent dynamic quality and control effect, stronger robustness and adaptability, and the running characteristics and stability can be maintained well under the situations of system disturbance and fault.