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.
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© 2007 Springer Berlin Heidelberg
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Wang, X., Dai, X. (2007). The ANN Inverse Control of Induction Motor with Robust Flux Observer Based on ESO. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_25
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DOI: https://doi.org/10.1007/978-3-540-72393-6_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
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