Application of neural network based fuzzy control to power system generator

The authors present an application of fuzzy control to a synchronous machine in a power system using the neural network theory. In this method, the membership function is determined by using the learning process of the neural network. For the RHS (right hand side) of fuzzy rules, they propose to use the optimal controls so that they can control the system even if the system is operated at some other operating points than the linearized point. The machine power output is considered as the change of operating points. Although the control using the proposed method is not so good as the control using the optimal control method at the linearized point, one can control the power system by the proposed method at wider ranges than the optimal control method.<>