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Induction Motor Adaptive Backstepping Control and Efficiency Optimization Based on Load Observer

Author

Listed:
  • Chuanguang Chen

    (College of Automation, Qingdao University, Qingdao 266071, China)

  • Haisheng Yu

    (College of Automation, Qingdao University, Qingdao 266071, China)

  • Fei Gong

    (College of Automation, Qingdao University, Qingdao 266071, China)

  • Herong Wu

    (College of Automation, Qingdao University, Qingdao 266071, China)

Abstract

In this paper, an adaptive load torque observer based on backstepping control is designed, which achieves accurate load estimation where the load is unknown. Based on this, in order to reduce the loss of the motor at low load, a smooth switching strategy of rotor flux based on speed error is designed. According to the real-time speed error of the induction motor, the smooth switching strategy achieves dynamic flux switching. Firstly, when the uncertain load occurs for the first time in the recursive design, the adaptive law of the load is designed, and a novel adaptive load torque observer is obtained, which accurately estimates the uncertain load torque in real time. Secondly, the relationship between the loss and the rotor flux is established by analyzing the loss model of induction motor, and the optimal rotor flux is obtained. The smooth switching control strategy based on speed error is designed to realize the efficiency optimization of induction motor. Finally, the control strategy proposed in this paper is experimentally verified on the LINKS-RT platform. The results show that the proposed control strategy has excellent load disturbance attenuation performance and reduces the energy loss.

Suggested Citation

  • Chuanguang Chen & Haisheng Yu & Fei Gong & Herong Wu, 2020. "Induction Motor Adaptive Backstepping Control and Efficiency Optimization Based on Load Observer," Energies, MDPI, vol. 13(14), pages 1-16, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3712-:d:386626
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    References listed on IDEAS

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    1. Kortas, Imen & Sakly, Anis & Mimouni, Mohamed Faouzi, 2017. "Optimal vector control to a double-star induction motor," Energy, Elsevier, vol. 131(C), pages 279-288.
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    Cited by:

    1. Elzbieta Szychta & Leszek Szychta, 2021. "Collective Losses of Low Power Cage Induction Motors—A New Approach," Energies, MDPI, vol. 14(6), pages 1-19, March.
    2. Anxing Liu & Haisheng Yu, 2020. "Smooth-Switching Control of Robot-Based Permanent-Magnet Synchronous Motors via Port-Controlled Hamiltonian and Feedback Linearization," Energies, MDPI, vol. 13(21), pages 1-16, November.
    3. Ming-Fa Tsai & Chung-Shi Tseng & Po-Jen Cheng, 2021. "Implementation of an FPGA-Based Current Control and SVPWM ASIC with Asymmetric Five-Segment Switching Scheme for AC Motor Drives," Energies, MDPI, vol. 14(5), pages 1-23, March.

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    1. Chuang, Ho-Chiao & Li, Guan-De & Lee, Chen-Ta, 2019. "The efficiency improvement of AC induction motor with constant frequency technology," Energy, Elsevier, vol. 174(C), pages 805-813.

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