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Fuzzy Luenberger Observer for Sensorless Control of Induction Motor Drive

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AETA 2022—Recent Advances in Electrical Engineering and Related Sciences: Theory and Application (AETA 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1081))

Abstract

The paper presents integration of fuzzy logic into adaptation mechanism of Luenberger observer for sensorless pulse width modulation-direct torque controlled (PWM-DTC) induction motor (IM) drive. At first, DTC strategy and PWM technique are described. Next, basic mathematical model for state representation, adaptive signal and proportional-integral (PI) adaptation mechanism of Luenberger observer is shown. However, the PI adaptation mechanism cannot ensure desired motor speed responses in both dynamic and steady-state operations of IM drive. Fuzzy logic control theory is added to overcome the disadvantage of PI adaptation mechanism via update proportional gain and integral constant time of PI controller. Simulations of sensorless control for two adaptation mechanisms are carried out at different reference speeds. Speed deviations are utilized to evaluate the performance of two adaptation mechanisms at both dynamic and steady-state operations. Theoretical assumptions of high performance of fuzzy logic are validated by assessments.

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Author information

Authors and Affiliations

  1. Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Quang Thanh Nguyen, Binh Ngoc Tran & Dung Quang Nguyen

  2. Department of Facility Management, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Trung Van Nguyen

  3. Modeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hau Huu Vo

  4. R&P Electronics Company Limited, Ho Chi Minh City, Vietnam

    Liem Dung Phan

  5. Faculty of Electrical Engineering and Computer Science, VSB–Technical University of Ostrava, Ostrava, Czechia

    Pavel Brandstetter

Authors
  1. Quang Thanh Nguyen
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  2. Trung Van Nguyen
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  3. Binh Ngoc Tran
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  4. Dung Quang Nguyen
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  5. Hau Huu Vo
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  6. Liem Dung Phan
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  7. Pavel Brandstetter
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Corresponding author

Correspondence to Hau Huu Vo .

Editor information

Editors and Affiliations

  1. Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Research Group, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Tran Trong Dao

  2. Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Vo Hoang Duy

  3. Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Ivan Zelinka

  4. Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Chau Si Thien Dong

  5. Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Phuong T. Tran

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Nguyen, Q.T. et al. (2024). Fuzzy Luenberger Observer for Sensorless Control of Induction Motor Drive. In: Trong Dao, T., Hoang Duy, V., Zelinka, I., Dong, C.S.T., Tran, P.T. (eds) AETA 2022—Recent Advances in Electrical Engineering and Related Sciences: Theory and Application. AETA 2022. Lecture Notes in Electrical Engineering, vol 1081. Springer, Singapore. https://doi.org/10.1007/978-981-99-8703-0_23

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