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• W1882634450 abstract "When flux and speed are measurable, the artificial neural network inverse system (ANNIS) can almost linearize and decouple (L&D) induction motor despite variation of parameters. In practice, the rotor flux cannot be measured and is difficult to estimate accurately due to parameters varying. The inaccurate flux can affect the ANNIS, coordinate transformation and outer rotor flux loop, and make the performance degrade further. Based on this, an artificial neural network inverse control (ANNIC) method of induction motor with robust flux observer based on extended state observer (ESO) is proposed. The observer can estimate the rotor flux accurately when uncertainty exists. The proposed control method is expected to enhance the robustness and improve the performance of whole control system. At last, the feasibility of proposed control method is confirmed by simulation." @default.
• W1882634450 created "2016-06-24" @default.
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• W1882634450 date "2007-07-16" @default.
• W1882634450 modified "2023-10-16" @default.
• W1882634450 title "The ANN Inverse Control of Induction Motor with Robust Flux Observer Based on ESO" @default.
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• W1882634450 doi "https://doi.org/10.1007/978-3-540-72393-6_25" @default.
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