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|Title:||A novel on line rotor resistance estimation technique using EA tuned fuzzy controller for vector controlled induction motor drive|
|Keywords:||Genetic Algorithm (GA)|
Indirect Field Oriented Vector Control (IFOC)
Induction motor (IM)
Mamdani fuzzy controller
Particle Swarm Optimization (PSO)
Proportional Integral (PI) controller
Rotor flux Model Reference Adaptive system (RF-MRAS)
|Abstract:||Induction motor with indirect field oriented control is well suited for high performance applications due to its excellent dynamic behavior. But, the indirect field oriented controller is sensitive to variations in rotor time constant, especially variation in rotor resistance. In this paper a scheme based on the Rotor flux Model Reference Adaptive Controller is used for on line identification of the rotor resistance and thus improving the steady state performance of the drive. The estimation of the actual rotor flux depends on the motor stator resistance, however its compensation is easier and the overriding feature of this estimation technique is the accurate identification of rotor resistance both during transient and steady state conditions when the drive is operating at full load and at zero motor speed condition. The effectiveness of the optimal designed Mamdani fuzzy controller based rotor identification scheme for four quadrant operation of motor drive is investigated and compared with the conventional trial and error based fuzzy controller in MATLAB/Simulink environment. � 2015 IEEE.|
|Appears in Collections:||Research Publications|
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