Abstract
This paper considers the vector control of double-fed induction generator in the presence of uncertainties. An electromagnetic torque controller and a rotor current controller are proposed based on an error transformation technique and a reduced-order extended state observer. Specifically, the error transformation technique is used to achieve the prescribed transient and steady performance. The reduced-order extended state observer is utilized to estimate and compensate for system uncertainties in real time. By using the proposed controllers, the tracking performance of the system is improved. Compared with the full-order extended state observer, the reduced-order extended state observer reduces the adjustment parameters, which renders it easier to implement in practice. The effectiveness of proposed scheme is validated via theoretical analysis and simulations.
D. Wang—This work was supported in part by the National Natural Science Foundation of China under Grants 61673081, 51579023, and in part by the Innovative Talents in Universities of Liaoning Province under Grant LR2017014, and in part by High Level Talent Innovation and Entrepreneurship Program of Dalian under Grant 2016RQ036, and in part by the National Key Research and Development Program of China under Grant 2016YFC0301500, and in part by the Fundamental Research Funds for the Central Universities under Grants 3132016313, 3132018306.
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Liu, Y., Li, H., Wu, W., Wang, D., Peng, Z. (2018). Prescribed Performance Control of Double-Fed Induction Generator with Uncertainties. In: Cheng, L., Leung, A., Ozawa, S. (eds) Neural Information Processing. ICONIP 2018. Lecture Notes in Computer Science(), vol 11307. Springer, Cham. https://doi.org/10.1007/978-3-030-04239-4_1
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DOI: https://doi.org/10.1007/978-3-030-04239-4_1
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