For automation requirements, it is important to have an adequate and accurate model of the system to be controlled in order to develop robust and efficient control algorithms. This model can be obtained through physical modelling using knowledge modelling techniques. However, several physical models are often difficult or impossible to develop. To overcome this difficulty, other methods based on a learning approach are adopted to develop representational models that describe the input-output behaviour of the process. This method is called dynamical identification.
This technical paper presents a dynamical identification of a direct-drive (DD) transverse flux (TF) permanent magnet synchronous generator (PMSG) based on a representational modelling approach. The use of TF PMSGs has become an attractive alternative for wind turbine systems. Indeed, these machines are characterized by a stronger relationship between the electromagnetic torque and the weight of active materials. The specific pole pair modular structure could eliminate or diminish the gear ratio compared to conventional wind turbines.