Simulation and Chaos Prediction of Wind Power Generator Based on Memristive LSTM Network

In this paper, the Memristive Long Short-Term Memory (MLSTM) algorithm is used to predict the chaos of the wind turbine system. Firstly, the model of the permanent magnet synchronous wind turbine system is established. At the same time, the Adomian algorithm is used to solve the numerical solution of the fractional-order system and draw the phase diagram. In addition, the MLSTM is exploited by replacing the neural network weight algorithm, and it is applied to the speed prediction of wind turbine system. The simulation results show that the MLSTM can effectively realise the forecast, offer suggestions for the management of a wind turbine system, and lay the foundation for directly implementing the memristor bathymetry algorithm using a memristor hardware circuit.