Intelligent controlled-wind-turbine emulator and induction-generator system using RBFN

A radial basis-function network (RBFN) is proposed for the intelligent control of a wind-turbine emulator and an induction-generator (IG) system with an AC/DC power converter. First, the indirect field-oriented mechanism is designed for the control of the IG system. Since the IG system is a nonlinear and time-varying dynamic system, an on-line trained RBFN is developed for the tracking controller of DC-link power to improve the control performance. The rotor speed of the IG, the DC-link voltage and current of the power converter are detected simultaneously to yield maximum power output of the converter through DC-link power control. Then, a closedloop wind-turbine emulator, also using the RBFN, is designed to produce the maximum power for the IG system at various wind speeds to confront the parameter dependency of the wind-turbine emulator. Further, some experimental results are provided to show the effectiveness of the proposed wind-turbine emulator and IG system using the RBFN controller. Finally, the control performance of the DC-link voltage control using the RBFN is also discussed.