الفهرس 
IntroductionOnly 14 pages are availabe for public view
 |  | from | 82 |  |  |
| | | from | 82 | | |
Abstract
The wide availability of microprocessors with much higher computational power capabilities has encouraged many researchers during the last decade to introduce the predictive control techniques to the field of power electronics and motor drives. One technique of predictive control, which is called model predictive control, is introduced in this work and its application to control multiphase induction motors is also presented. Mathematical formulation of both model predictive torque control and model predictive speed control algorithms are explained for both three-phase and five-phase machines, which shows that the algorithms’ equations are intuitive so they can be easily understood or implemented. Since a load torque estimate is needed in the predictive speed controller, an observer based on the minimal-order Gopinath’s method is designed to get the load torque value. A comparison between the two techniques is carried out based on a simulation study. Predictive control can be employed in the field of electric drives in different ways. It may be used within the controller structure of field-oriented control or direct torque control methods. Otherwise, it might also be used by itself as a method of control, as presented in this study. The stator currents may be used as the controlled variables, and then it is called predictive current control, whereas the electromagnetic torque or rotor speed could also be used directly as the controlled variables, thus yielding predictive torque control or predictive speed control, respectively. The model for predicting the controlled variables and estimating the unmeasured variables in both techniques is derived in a space vector form. Whereas, the model for the five-phase induction motor is also built using the equations in the dqxy0 reference frame. The discretization of the models’ equations is performed by using the Euler backward and forward methods.