We consider a Double Fed Induction Generator (DFIG) based wind energy conversion system with highly nonlinear dynamics and abrupt changes as a test bed for optimally extracting wind energy. Dynamic backstepping is utilized to implement a sliding mode control that combines high order sliding mode control and Multi-Input/Multi-Output (MIMO) backstepping. A novel adaptive estimator is utilized to obtain the maximum active and reactive output power in the presence of stochastic wind velocity profiles which are fed as the reference signals to the algorithm. The controller developed is tuned and evaluated on a simulator of the DFIG based wind power conversion system; which is subsequently implemented on an experimental setup. Experimental results show that the proposed adaptive method outperforms the traditional control methods in terms of robustness and performance.

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