Neural network based on excitation controller design of power systems via backstepping

In this paper, for a class of strict feedback nonlinear system with single input single output (SISO), a kind of adaptive controller based on radial basis function (RBF) neural networks is designed via backstepping method. A virtual controller is designed in every step of backstepping by choosing a suitable Lyapunov function. In the last step, the real controller will be synthesized. Such designed controller can assure the stability of the closed loop system. By applying the controller designing method to an excitation system of a power system, an adaptive excitation controller of a power system is designed. Some simulation shows the validity of the proposed method.