The paper combines two major neuro-fuzzy applications in power engineering: stabilizing power systems at a generation stage and reducing disturbances at a delivery stage. It presents a neural-fuzzy classifier for recognition of power disturbances and a fuzzy excitation controller comprising both the exciter and the power system stabilizer.

This paper proposes a Neuro-Fuzzy Controller to Thyristor Controlled Series Capacitor (TCSC), which might have a significant impact on power system dynamics. We tune the scaling factors of neuro-fuzzy controller using adaptive critic. The proposed method is used for damping the low frequency oscillations caused by disturbances such as a sudden change of small or large loads or an outage in the ...

Static Synchronous Series Compensator (SSSC) is a series compensating Flexible AC Transmission System (FACTS) controller for maintaining to the power flow control on a transmission line by injecting a voltage in quadrature with the line current and in series mode with the line. In this work, an Adaptive Network-based Fuzzy Inference System controller (ANFISC) has been proposed for controlling o...

In this paper, a multi agent controller for meeting different criteria, based on neuro-fuzzy controller is presented. The proposed controller is motivated by the affective and emotional faculties in human begins, which constantly evaluate the current states with respect to the achievement of the desired goals. For meeting different criteria, the controller consists of several critic agents that...

A static synchronous compensator (STATCOM) is generally used to regulate voltage and improve transient stability in transmission and distribution networks. This is achieved by controlling reactive power exchange between STATCOM and the grid. Unbalanced sags are the most common type of voltage sags in distribution networks. A static synchronous compensator (STATCOM) is generally used to maintain...

In this paper, a novel controller for brushless DC (BLDC) motor has been presented. The proposed controller is based on Adaptive Neuro-Fuzzy Inference System (ANFIS) and the rigorous analysis through simulation is performed using simulink tool box in MATLAB environment. The performance of the motor with proposed ANFIS controller is analyzed and compared with classical Proportional Integral (PI)...