4.7 Article

An Adaptive Active Disturbance Rejection Control Strategy for Speed-Sensorless Induction Motor Drives

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TTE.2022.3148412

Keywords

Estimation; Rotors; Induction motor drives; Phase locked loops; Motor drives; System dynamics; Transportation; Adaptive active disturbance rejection control (ADRC); induction motor drives; speed estimation scheme; state error feedback control rate (SEFCR); third-order adaptive extended state observer (AESO)

Funding

  1. High-Speed Railway Joint Funds of the National Natural Science Foundation of China [U1934204]
  2. National Natural Science Foundation of China [52177060]

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This article proposes an adaptive active disturbance rejection control strategy for speed-sensorless induction motor drives. By using an adaptive ESO to estimate the speed and disturbance, as well as using a speed controller and a closed-loop flux observer to improve system dynamics, better control performance is achieved.
Speed-sensorless control of induction motor drives based on the extended state observer (ESO) attracts much popularity due to its key characteristics, e.g., satisfactory estimation performance, and high robustness against disturbances. However, the conventional ESO generally uses fixed high gains to achieve fast convergence. This may bring about the concern of noise sensitivity. Moreover, a proportional-integral (PI)-type speed controller is mostly adopted in speed-sensorless control of induction motor drives, which may cause unsatisfactory system dynamics. To address these, an adaptive active disturbance rejection control (ADRC) strategy is proposed for speed-sensorless induction motor drives in this article. In this scheme, a third-order adaptive ESO (AESO) is first used to estimate the speed, the phase, and the overall disturbance. Then, a speed controller based on the state error feedback control rate (SEFCR) is designed to improve system dynamics. In practice, disturbances like dc offsets may further challenge estimation performance, and hence, a closed-loop flux observer (CLFO) is employed to deal with this issue. Additionally, a parameter sensitivity analysis of the CLFO is also provided to evaluate the performance of the proposed scheme. Finally, extensive experimental tests have been carried out to validate the effectiveness of the proposed.

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