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http://dx.doi.org/10.6113/JPE.2015.15.3.730

MRAS Speed Estimator Based on Type-1 and Type-2 Fuzzy Logic Controller for the Speed Sensorless DTFC-SVPWM of an Induction Motor Drive  

Ramesh, Tejavathu (Department of Electrical Engineering, National Institute of Technology Kurukshetra)
Panda, Anup Kumar (Department of Electrical Engineering, National Institute of Technology Rourkela)
Kumar, S. Shiva (Department of Electrical Engineering, National Institute of Technology Rourkela)
Publication Information
Journal of Power Electronics / v.15, no.3, 2015 , pp. 730-740 More about this Journal
Abstract
This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.
Keywords
Direct Torque and Flux Control; Induction Motor Drive; Model Reference Adaptive System; Type-1 Fuzzy Logic Controller; Type-2 Fuzzy Logic Controller;
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