- Improving the efficiency of synchronous generators is crucial for achieving significant energy savings in global electricity production, given that they contribute to approximately 95% of the world’s power generation. This article explores the topic of controlling synchronous generators, providing a thorough theoretical foundation and simulation-based control strategies along with a complete framework. The synchronous generator model is first linearized and then state feedback control strategies are used. The research smoothly shifts to exploring neuro-fuzzy control, noting that linear models are not sufficient for describing the complexities observed in the

behavior of synchronous generators. The neuro-fuzzy controller was developed to address the system’s non-linearities. Its improved performance is a result of its ability to simulate complex, non-linear systems better than conventional approaches. Nonlinearities are addressed by combining neuro-fuzzy intelligence with linear control. Stability and precision are improved by a control law that has been derived to counteract nonlinearities. The study highlights the neuro-fuzzy controller’s adaptive characteristics in obtaining accurate output control under difficult nonlinear behavior in the generator system.

Index Terms- Neuro-Fuzzy, State feedback, Linear model, Nonlinear model, Lyapunov Stability