scholarly journals Use of neuro-fuzzy logic in tool selection and cost estimation in CNC manufacturing of prototypes

2006 ◽  
pp. 135-150
Author(s):  
L. Chiang ◽  
C. Fantozzi ◽  
M. Granchi ◽  
E. Vettori
Keyword(s):  
Fuzzy Logic ◽  
Cost Estimation ◽  
Tool Selection ◽  
Neuro Fuzzy

Smoothing the output power of a wind energy conversion system using a hybrid nonlinear pitch angle controller

2021 ◽  
pp. 014459872110417
Author(s):  
Ya-Jun Fan ◽  
Hai-tong Xu ◽  
Zhao-Yu He
Keyword(s):  
Fuzzy Logic ◽  
Wind Energy ◽  
Output Power ◽  
Wind Turbines ◽  
Fuzzy Inference System ◽  
Pitch Angle ◽  
Fuzzy Inference ◽  
Hybrid Control ◽  
Inference System ◽  
Neuro Fuzzy

Wind energy has been developed and is widely used as a clean and renewable form of energy. Among the existing variety of wind turbines, variable-speed variable-pitch wind turbines have become popular owing to their variable output power capability. In this study, a hybrid control strategy is proposed to implement pitch angle control. A new nonlinear hybrid control approach based on the Adaptive Neuro-Fuzzy Inference System and fuzzy logic control is proposed to regulate the pitch angle and maintain the captured mechanical energy at the rated value. In the controller, the reference value of the pitch angle is predicted by the Adaptive Neuro-Fuzzy Inference System according to the wind speed and the blade tip speed ratio. A proposed fuzzy logic controller provides feedback based on the captured power to modify the pitch angle in real time. The effectiveness of the proposed hybrid pitch angle control method was verified on a 5 MW offshore wind turbine under two different wind conditions using MATLAB/Simulink. The simulation results showed that fluctuations in rotor speed were dramatically mitigated, and the captured mechanical power was always near the rated value as compared with the performance when using the Adaptive Neuro-Fuzzy Inference System alone. The variation rate of power was 0.18% when the proposed controller was employed, whereas it was 2.93% when only an Adaptive Neuro-Fuzzy Inference System was used.

Application of Neuro-Fuzzy Logic for Early Detection and Diagnostics in Gas Plants and Combustion Chambers at ENEA

2002 ◽  
pp. 319-333
Author(s):  
Massimo Sepielli ◽  
P. Carmelo Incalcaterra ◽  
Massimo Presaghi ◽  
Paolo F. Fantoni ◽  
Davide Roverso
Keyword(s):  
Fuzzy Logic ◽  
Early Detection ◽  
Combustion Chambers ◽  
Neuro Fuzzy ◽  
Gas Plants
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