A dead-beat estimator for on-line identification of non-linear equivalent parameters of brushless machines

The development of fast and powerful microprocessors and Digital Signal Processors (DSPs), have over the last decade increased and extended the application of model predictive control for Power Electronics and Drives. In permanent magnet synchronous motor drives(PMSM),especially for a Dead-Beat control, accurate knowledge of machine parameters has advantage in its control and/or monitoring its condition. In this thesis a new method for on-line identification of PMSM parameters for a dead beat current control is proposed. The on-line adaptation helps tracking any dynamic change in the motor parameters due the enviromental, aging and loading condition. The motor parameters used in the controller can be updated to enhance the performance. Furthermore a traditional Recoursive least squares method is implemented in this thesis to show the performances.