Speed Control for Multi-phase Induction Machine Fed by Multi-level Converters Using New Neuro-Fuzzy

被引：2

作者：

Zaidi, E. ^{[1
]}

Marouani, K. ^{[1
]}

Bouadi, H. ^{[1
]}

机构：

[1] Ecole Mil Polytech, LCM UER ELT, Bordj El Bahri 16046, Algeria

来源：

RENEWABLE ENERGY FOR SMART AND SUSTAINABLE CITIES: ARTIFICIAL INTELLIGENCE IN RENEWABLE ENERGETIC SYSTEMS | 2019年 / 62卷

关键词：

Multi-phase induction machine (MPIM); Multi-level converters (MLC); Neuro-fuzzy controller (NFC); DIRECT TORQUE CONTROL; NETWORK;

D O I：

10.1007/978-3-030-04789-4_49

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper proposes a novel neuro-fuzzy control (NFC) for multi-phase induction machine (MPIM) fed by two multi-level converters (MLC) using venturing modulation algorithm. A four-layer artificial neural network (ANN) structure is utilized to train the parameters of the fuzzy logic controller (FLC) based on the minimization of the square of the error. In the proposed method indirect field oriented control (IFOC) is applied to the MPIM. The results are compared with the results obtained from a proportional-integral (PI) controller. Simulation results obtained are very satisfactory and showed that neuro-fuzzy control performance is enhanced using two multi-level converters (MLC) with introduces load disturbances.

引用

页码：457 / 468

页数：12

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