In this paper, we propose a design technique for a neural network controller and apply it to power system stabilization. Using a learning algorithm of error back propagation that accepts error and change of error as inputs, the momentum learning technique is used by which reduction of learning time is possible for real time control. The related simulation results show that the proposed control techinque is more powerful than the conventional ones for dynamic responses.