scholarly journals Adaptive neuro fuzzy inference system based decoupled control for neutral point clamped multi level inverter fed induction motor drive

2021 ◽  
Vol 7 (2) ◽  
pp. 70-82
Author(s):  
Giribabu Dyanamina ◽  
Sanjay Kumar Kakodia
Keyword(s):  
Induction Motor ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Neutral Point ◽  
Motor Drive ◽  
Induction Motor Drive ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Decoupled Control ◽  
Multi Level

A Novel Neuro-Fuzzy Inference System with Multi-Level Membership Function for Classification Applications

2007 ◽  
Vol 11 (4) ◽  
pp. 365-372 ◽  
Author(s):  
Cheng-Jian Lin ◽  
◽  
Chi-Yung Lee ◽  
Cheng-Hung Chen ◽  
Keyword(s):  
Membership Function ◽  
Fuzzy Inference System ◽  
Clustering Algorithm ◽  
Fuzzy Inference ◽  
Learning Algorithm ◽  
Layer Structure ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Multi Level ◽  
Takagi Sugeno

In this paper, a novel neuro-fuzzy inference system with multi-level membership function (NFIS_MMF) for classification applications is proposed. The NFIS_MMF model is a five-layer structure, which combines the traditional Takagi-Sugeno-Kang (TSK). Layer 2 of the NFIS_MMF model contains multi-level membership functions, which are multilevel activation functions. A self-constructing learning algorithm, which consists of the self-clustering algorithm (SCA), fuzzy entropy, and the backpropagation algorithm, is also proposed to construct the NFIS_MMF model and perform parameter learning. Simulations were conducted to show the performance and applicability of the proposed model.

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