Rotor resistance estimation for induction motor using model reference adaptive controller

<span>Fuzzy logic controller (FLC) has shown excellent performance in dealing with the non-linearity and complex dynamic model of the induction motor. However, a conventional constant parameter FLC (CPFL) will not be able to provide–good coverage performance for a wide speed range operation with a single tuning parameter. Therefore, this paper proposed a self tuning mechanism FLC approach by model reference adaptive controller (ST-MRAC) to continuously allow to adjust the parameters. Due to real time hardware application, the dominant rules selection method for simplified rules has been implemented as part of the reducing computational burden. Experiment results validate a good performance of the ST-MRAC compared to the CPFL for the speed performance in terms of the wide range of operations and disturbance showed remarkable performance.</span>

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Sensorless Speed Control of Induction Motor Driven Electric Vehicle Using Model Reference Adaptive Controller

Energy Procedia ◽

10.1016/j.egypro.2016.11.222 ◽

2016 ◽

Vol 90 ◽

pp. 540-551 ◽

Cited By ~ 5

Author(s):

Abhisek Pal ◽

Rakesh Kumar ◽

Sukanta Das

Keyword(s):

Induction Motor ◽

Electric Vehicle ◽

Speed Control ◽

Adaptive Controller ◽

Model Reference ◽

Model Reference Adaptive

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Model Reference Adaptive System for the Online Rotor Resistance Estimation in the Slip-Ring Machine Based Test-bench

Periodica Polytechnica Electrical Engineering and Computer Science ◽

10.3311/ppee.12495 ◽

2018 ◽

Vol 62 (4) ◽

pp. 149-154

Author(s):

Tamás Égető ◽

Balázs Farkas

Keyword(s):

Test Bench ◽

Adaptive System ◽

Model Reference ◽

Stator Current ◽

Model Reference Adaptive System ◽

Rotor Resistance ◽

Slip Ring ◽

Stator Flux ◽

Rotor Resistance Estimation ◽

Model Reference Adaptive

Motor control algorithms with high dynamics are generally based on two basic approach field oriented control (FOC) and direct torque control (DTC). The idea of the first one is to decompose the stator current based on the rotor flux, the second one controls the torque based on the stator flux. Therefore, the FOC is very sensitive to the parameter accuracy regarding the drive performance. That is why it is crucial to verify the parameter identification in the real environment. On the other hand, the parameter sensitivity of DTC is much smaller since the stator flux estimation requires only the knowledge of the stator resistance. The article focuses on the verification of rotor resistance identification in the FOC based drive system by means of the slip ring machine based test bench. The recommended procedure calculates the torque based on the stator current and flux to implement model reference adaptive system for online rotor resistance estimation without signal injection.

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Speed and Rotor Resistance Estimation of AC Induction Motor

MATEC Web of Conferences ◽

10.1051/matecconf/201817302037 ◽

2018 ◽

Vol 173 ◽

pp. 02037

Author(s):

Wang Dafang ◽

Wang Miaoran ◽

Dong Guanglin ◽

Wei Hui ◽

Xu Zexu

Keyword(s):

Induction Motor ◽

Reactive Power ◽

Estimation Method ◽

Adaptive Controller ◽

High Accuracy ◽

Identification Accuracy ◽

Speed Sensorless ◽

Rotor Resistance ◽

Model Reference Adaptive ◽

Ac Induction Motor

The speed estimation method based on Extended Kalman Filter (EKF) is widely used in speed sensorless induction motor. The method has high accuracy and good robustness. However, EKF is sensitive to parameters. In particular, the rotor resistance becomes up to twice the original when the motor is running. This greatly affects the speed identification accuracy. This paper achieves online estimation of rotor resistance utilizing the Model Reference Adaptive Controller (MRAC) based on reactive power. This ensures that the speed is estimated with high accuracy even if the rotor resistance changes suddenly. Simulation results have been presented to verify the effectiveness of the method.

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