ANFIS robust control application and analysis for load frequency control with nonlinearity

This study investigates and demonstrates the adaptive neuro-fuzzy inference system (ANFIS) controller performance on a dynamic system with inherent nonlinearity. Here, dynamics of automatic load frequency control is considered under this case. The ANFIS controller is designed, trained, and optimized to regulate the frequency deviation of an isolated power delivery area. The frequency deviation data under a sample disturbance are taken with the desired control effort and are picked to train with five different membership functions. The tuning is carried out by the hybrid method. The ANFIS controller, developed, yields a better result, with less settling time of up to 20 s than the standard disturbance rejection proportional–integral–derivative (PID) controller takes. Designed ANFIS performs very robustly considering variations in inertia and damping. All the experimental setup is built under a MATLAB Simulink environment.