Parameter Sensitivity and Estimation of a Novel Hybrid Scheme Based on MRAS in Indirect Vector Control System

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Abstract:

The indirect vector control scheme is machine parameter dependent. And parameter identification schemes are themselves dependent on some motor parameters. This paper analyzes parameter sensitivities of two identification methods, reactive power model and q-axis flux model based on MRAS are analyzed through extensive simulations and experiments on an induction motor. Then a novel scheme is proposed based on hybrid model by combining the two adaptive models. The results demonstrate that the hybrid scheme is almost parameter independent in different operation conditions. And it is considered useful in practical application.

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148-151

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August 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Bose B K. Modern power electronics and AC drives [M]. Beijing:China Machine Press, (2005).

Google Scholar

[2] Suman Maiti, Chandan Chakraborty, Yoichi Hori, et al. Model Reference Adaptive Controller-Based Rotor Resistance and Speed Estimation Techniques for Vector Controlled Induction Motor Drive Utilizing Reactive Power [J]. IEEE Transactions on Industrial Electronics , 2008, 55(2): 594-601.

DOI: 10.1109/tie.2007.911952

Google Scholar

[3] Fan Yang, Qu Wenlong, Lu Haifeng, et al. Slip frequency correction method base on rotor flux q axis component for induction machine indirect vector control system[J]. CSEE, 2009, 29(9): 62-66.

Google Scholar

[4] A. Larabi, M.S. Boucherit. Robust Speed-Sensorless Induction Motor with the rotor Time Constant Adaptation [C]. Electrical Systems for Aircraft,Railway and Ship Propulsion, 2010: 1-6.

DOI: 10.1109/esars.2010.5665240

Google Scholar

[5] Godpromesse Kenn'e, Tarek Ahmed Ali, et al. Real-time speed and flux adaptive control of induction motors using unknown time-varying rotor resistance and load torque[J]. IEEE Transactions on Energy Conversion, 2009, 24(2): 375-387.

DOI: 10.1109/tec.2008.926042

Google Scholar

[6] F. Lima, W. Kaiser, I. N. da Silva, et al. Speed Neuro-fuzzy Estimator Applied To Sensorless Induction Motor Control [J]. IEEE Latin America Transactions, 2012, 10(5): 2065-(2073).

DOI: 10.1109/tla.2012.6362350

Google Scholar