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DC Field | Value | Language |
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dc.contributor.author | Rajendran, S. | |
dc.contributor.author | Jena, D. | |
dc.date.accessioned | 2020-03-31T08:48:10Z | - |
dc.date.available | 2020-03-31T08:48:10Z | - |
dc.date.issued | 2014 | |
dc.identifier.citation | Journal of Modern Power Systems and Clean Energy, 2014, Vol.2, 2, pp.114-125 | en_US |
dc.identifier.uri | 10.1007/s40565-014-0061-3 | |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/13521 | - |
dc.description.abstract | This paper presents a nonlinear control approach to variable speed wind turbine (VSWT) with a wind speed estimator. The dynamics of the wind turbine (WT) is derived from single mass model. In this work, a modified Newton Raphson estimator has been considered for exact estimation of effective wind speed. The main objective of this work is to extract maximum energy from the wind at below rated wind speed while reducing drive train oscillation. In order to achieve the above objectives, VSWT should operate close to the optimal power coefficient. The generator torque is considered as the control input to achieve maximum energy capture. From the literature, it is clear that existing linear and nonlinear control techniques suffer from poor tracking of WT dynamics, increased power loss and complex control law. In addition, they are not robust with respect to input disturbances. In order to overcome the above drawbacks, adaptive fuzzy integral sliding mode control (AFISMC) is proposed for VSWT control. The proposed controller is tested with different types of disturbances and compared with other nonlinear controllers such as sliding mode control and integral sliding mode control. The result shows the better performance of AFISMC and its robustness to input disturbances. In this paper, the discontinuity in integral sliding mode controller is smoothed by using hyperbolic tangent function, and the sliding gain is adapted using a fuzzy technique which makes the controller more robust. � 2014, The Author(s). | en_US |
dc.title | Variable speed wind turbine for maximum power capture using adaptive fuzzy integral sliding mode control | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
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