Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A neuro-fuzzy controller for speed control of a permanent magnet synchronous motor drive
Expert Systems with Applications: An International Journal
A novel approach for ANFIS modelling based on full factorial design
Applied Soft Computing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An adaptive neuro-fuzzy inference system for bridge risk assessment
Expert Systems with Applications: An International Journal
Hybrid intelligent scenario generator for business strategic planning by using ANFIS
Expert Systems with Applications: An International Journal
Modelling and simulation of an autonomous variable speed micro hydropower station
Mathematics and Computers in Simulation
Hi-index | 12.05 |
The power from wind varies depending on the environmental factors. Many methods have been proposed to locate and track the maximum power point (MPPT) of the wind, such as the fuzzy logic (FL), artificial neural network (ANN) and neuro-fuzzy. In this paper, a variable-speed wind-generator maximum-power-point-tracking (MPPT) based on adaptative neuro-fuzzy inference system (ANFIS) is presented. It is designed as a combination of the Sugeno fuzzy model and neural network. The ANFIS model is used to predict the optimal speed rotation using the variation of the wind speed as the input. The wind energy conversion system (WECS) employing a permanent magnet synchronous generator connected to a DC bus using a power converter is presented. A wind speed step model was used in the design phase. The performance of the WECS with the proposed ANFIS controller is tested for fast wind speed variation. Simulation results showed the possibility of achieving maximum power tracking for the wind and output voltage regulation for the DC bus simultaneously with the ANFIS controller. The results also proved the good response and robustness of the control system proposed.