| Autor: |
Mendaz, Kheira, Bendaoud, Abdelber |
| Předmět: |
|
| Zdroj: |
Electrotehnica, Electronica, Automatica; 2019, Vol. 67 Issue 1, p35-45, 11p |
| Abstrakt: |
Induction motors are mainly preferred in many applications. These machines are subjected to several internal and external stresses, which result in different kinds of faults. This article is related to faults that can appear in multilevel inverters (five level inverter) associated with asynchronous motor, which have a high number of components. This is a subject of increasing importance in high-power inverters. The application of artificial intelligence has become an important topic in electric machine control and it has become a soft computed tool for solving concerns having un-known solution. It is a soft computed formation of hybrid model by a neuron fuzzy developing system in which fuzzy inference system is effectively trained by a neural learning characterization, so this study interested of two Controllers for speed regulation of induction machine, the sliding adaptive Neural Fuzzy Inference controller (SANFIS) and sliding mode controller without existence of switch fault to compare their performance of each controller on the physical parameters of the machine (speed, electromagnetic torque and current) and with existence of switch fault of five level inverter associated with induction machine, to show the effects of this fault their on the physical parameters of the induction machine. Simulation study has been carried out using the MATLAB/Simulink environment to verify the robustness of the power electronics converters and the effectiveness of proposed control method under steady state and transient conditions and machine parameters mismatches. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
