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Speed and flux observer based on adaptive linear neuron for induction motor

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Abstract

The robustness and economy of the induction motor drive system can be improved by a high-precision observation algorithm instead of an encoder. Such an algorithm is adopted to obtain the speed and flux linkage of the induction motor. In this paper, an adaptive linear neuron speed digital observer for the induction motor is proposed. First, discrete voltage and current models are established. Then, a novel speed and rotor flux digital observer based on the adaptive linear neuron with less calculation complexity is presented. This observer contains a hidden layer and two input signals that can work with the rotor flux error and the deviation of the error. The adaptive learning method of the weight coefficients described by the difference equation is presented. Finally, a simulation and an experiment are conducted to certify the correctness and effectiveness of the proposed adaptive linear neuron speed digital observer.

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Funding

This work was supported by Hunan Provincial Natural Science Foundation of China (2022JJ60035).

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Authors and Affiliations

  1. School of Electrical Engineering, Hunan Industry Polytechnic, Changsha, Hunan, China

    Liangbin Liu & Deyu Liu

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  1. Liangbin Liu
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  2. Deyu Liu
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Correspondence to Deyu Liu.

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Liu, L., Liu, D. Speed and flux observer based on adaptive linear neuron for induction motor. J. Power Electron. 23, 1379–1388 (2023). https://doi.org/10.1007/s43236-023-00675-3

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  • DOI: https://doi.org/10.1007/s43236-023-00675-3

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