Improved Backstepping Control of a DFIG based Wind Energy Conversion System using Ant Lion Optimizer Algorithm

In this paper, an improved Backstepping control based on a recent optimization method called Ant Lion Optimizer (ALO) algorithm for Doubly Fed Induction Generator (DFIG) driven by wind turbine is designed and presented. ALO applied obtaining optimum (BCS) parameters that are able to make the drive more robust with faster dynamic response, higher accuracy steady performance. The fitness function of be minimized using some indexes criterion like Integral Time Absolute Error (ITAE) Square (ITSE). Simulation tests carried out in MATLAB/Simulink environment validate effectiveness proposed BCS-ALO compared conventional BCS control. results prove objectives paper were accomplished terms robustness, better efficiency, reduced harmonic distortion, minimization stator powers ripples performing well solving problem uncertainty model parameter.