Application of mind evolutionary computation based fuzzy neural network in variable-speed wind turbines

To satisfy the requirements of widely operational range of rotor speed, high nonlinearity and time variant characteristics in variable-speed wind turbines, a system with a fuzzy neural network controller based on mind evolutionary computation (MEC) optimization was designed. The controller combined the advantage of fast searching optimization of MEC and the advantage of not depending on controlled plant of fuzzy neural network controller. This method uses MEC to search the optimal mean, the optimal standard deviation and the optimal weights that connect membership layer and rule layer, and the fuzzy neural network controller has good control performance. Simulation and experimental results verified the effectiveness of the method that based on mind evolutionary fuzzy neuron (MEFN) controller. The results show that this method has good control effect on system regulating. For variable-speed wind turbines system in practice, this method has has excellent adaptability and robustness.