Adaptive dynamic sliding mode controller based on extended state observer for brushless doubly fed induction generator
Brushless doubly fed induction generators are widely used in wind turbines and have a nonlinear and complex structure. There are many uncertainties and unmodeled dynamics in the state-of-the-art models presented for these systems. In this article, nonlinear and robust control theory based on the sli...
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Published in | International journal of dynamics and control Vol. 12; no. 10; pp. 3719 - 3732 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.10.2024
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 2195-268X 2195-2698 |
DOI | 10.1007/s40435-024-01459-8 |
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Summary: | Brushless doubly fed induction generators are widely used in wind turbines and have a nonlinear and complex structure. There are many uncertainties and unmodeled dynamics in the state-of-the-art models presented for these systems. In this article, nonlinear and robust control theory based on the sliding mode method is considered for these generators. A dynamic type of sliding mode controller is used to produce a smooth and implementable control signal. The dynamic sliding mode method, although produces a smooth control signal, it needs the upper bound of the uncertainty and its derivative. Therefore, this problem has been solved by adapting controller gains in this article. Another problem of the dynamic sliding mode method is the increase in the demand for data, including the need for the derivative of the sliding variable. To solve this problem, the extended state observer has been used in this research. In addition, the finite-time stability of the closed-loop system has been proved. The performance of the proposed control method has been evaluated by applying computer simulation on an accurate model of a brushless doubly fed induction generator used in a wind turbine. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 2195-268X 2195-2698 |
DOI: | 10.1007/s40435-024-01459-8 |