Nonlinear model identification and control of wind turbine using wavenets

In this paper a PI control strategy using neural network adaptive RASP1 wavelet for WECS's control is proposed. It is based on single layer feed forward neural networks with hidden nodes of adaptive RASPl (rational functions with second-order) wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. This particular neuro PI controller assumes a certain model structure to approximately identify the system dynamics of the unknown plant (WECSs) and generate the control signal. The results are applied to a typical turbine/generator pair, showing the feasibility of the proposed solution