Enhanced Sensorless Backstepping Control of Brushless Doubly Fed Reluctance Generators Using an Adaptive High-Gain Observer

This study proposes a strategy for managing wind-turbine energy systems through the utilization of a high-gain observer in a sensorless backstepping control method applied to brushless double-fed reluctance generators (BDFRG). The paper initially introduces a vector control technique for brushless doubly fed reluctance generators, followed by the integration of the backstepping control method and the high-gain observer strategy within the overall system. Moreover, the research investigates the “maximum torque per inverter ampere” strategy, which enables the brushless doubly fed reluctance generators to achieve full magnetization by the primary winding, resulting in a reduction in the power factor. The stability of the system is established through the application of the Lyapunov theory. The simulation outcomes validate the efficacy and importance of this approach.