Study the robustness of automatic voltage regulator for synchronous generator based on neuro-fuzzy network

Abstract EN

Modern power systems are complex and non-linear and their operating conditions can vary over a wide range, and since neuro - fuzzy network can be used as intelligent controllers to control non-linear dynamic systems through learning, which can easily accommodate the non-linearity, time dependencies, model uncertainty and external disturbances.

A Neuro-Fuzzy model system is proposed as an effective neural network controller model to achieve the desired robust Automatic Voltage Regulator (AVR) for Synchronous Generator (SG) to maintain constant terminal voltage.

The concerned Neuro-fuzzy controller for AVR is examined on different models of SG and loads.

The results show that the Neuro-Fuzzy -controllers have excellent responses for all SG models and loads in the view point of transient response and system stability compared with optimal PID controllers tuned by practical swarm optimization.

They also show that the margins of robustness for Neuro-Fuzzy -controller are greater than PID controller.