Application of model reference adaptive control with signal adaptation to PM brushless DC motor drives

The performance of permanent magnet brushless DC motor (PMBDCM) drives degrades with parameter and load variations. An overview of adaptive methods and advantages of model reference adaptive control in the context of providing a solution to these problem, is presented. Model reference adaptive control in general form and modified signal adaptation algorithms are introduced. Model reference adaptive control with signal adaptation algorithms has been applied to compensate parameter sensitivity and influence of load torque in it permanent magnet brushless DC motor (PMBDCM) drive. Dynamic simulation results show significant reduction in the error caused by variations in parameters and load torque.