Article ID Journal Published Year Pages File Type
5004435 ISA Transactions 2015 14 Pages PDF
Abstract

•The MRAS based speed sensorless direct Torque and flux control of an IMD is presented.•The Type-1 and new Type-2 FLC based adaptation mechanism schemes are implemented.•The performances of various control schemes are carried out in a MATLAB/Simulink.•The simulation results of an IMD are presented under different operating conditions and compared.•The simulation results are validated with experimental prototype results.

In this research study, a model reference adaptive system (MRAS) speed estimator for speed sensorless direct torque and flux control (DTFC) of an induction motor drive (IMD) using two adaptation mechanism schemes are proposed to replace the conventional proportional integral controller (PIC). The first adaptation mechanism scheme is based on Type-1 fuzzy logic controller (T1FLC), which is used to achieve high performance sensorless drive in both transient as well as steady state conditions. However, the Type-1 fuzzy sets are certain and unable to work effectively when higher degree of uncertainties presents in the system which can be caused by sudden change in speed or different load disturbances, process noise etc. Therefore, a new Type-2 fuzzy logic controller (T2FLC) based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties and improves the performance and also robust to various load torque and sudden change in speed conditions, respectively. The detailed performances of various adaptation mechanism schemes are carried out in a MATLAB/Simulink environment with a speed sensor and speed sensorless modes of operation when an IMD is operating under different operating conditions, such as, no-load, load and sudden change in speed, respectively. To validate the different control approaches, the system also implemented on real-time system and adequate results are reported for its validation.

Related Topics
Physical Sciences and Engineering Engineering Control and Systems Engineering
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