Power system stabilization using fuzzy-neural hybrid intelligent control

This paper presents fuzzy-neural hybrid control for power system stabilization. PID controller is still dominant in controlling of most industrial systems. The reason of such popularity is that detailed knowledge about the system is not required but the controller can be tuned by means of simple rules of thumb. The main idea of hybrid control is that the dynamic feedforward compensator can be used for improving the ability to track the reference rather than changing the dynamics, while feedback is used for stabilizing the system and for suppressing disturbances. In this paper, fuzzy logic is applied to design a feedback controller and then neural network inverse model is obtained for a feedforward compensator. The controller is tested for one-machine infinite-bus power system for various operating conditions.