Abstract-Model predictive control algorithms have recently gained more importance in the field of ١٥ wind power generators. One of the important categories of model predictive control methods is improved ١٦ deadbeat control in which the reverse model of generator is used to calculate the appropriate inputs for the ١٧ next iteration of controlling process. In this paper, a new improved deadbeat algorithm is proposed to ١٨ control the stator currents of an outer-rotor five-phase BLDC generator. Extended Kalman filter is used in ١٩ the estimation step of proposed method, and generator equations are used to calculate the appropriate generators, brushless direct current (BLDC) generators have the advantage of higher torque density,
٣٢simpler winding distribution and more fault tolerance [1]. As a result, these machines are a practical option
٣٣for low-maintenance and high power applications such as off-shore wind power farms. Several methods
٣٤are proposed in literature to have a better control on stator phase currents of BLDC generators.
٣٥Among these algorithms, model predictive control (MPC) has become a suitable option recently. MPC
٣٦concept is easy to understand, and various constraints and nonlinearities can be directly included in its ٣٧ structure. Moreover, the resulting controller is easy to implement [2], [3]. These types of controllers can be ٣٨ effectively implemented in generator controlling algorithm because linear models of BLDC generators are
٣٩quite well known and developed through analytical methods.
٤٠In the field of generator power control, MPC algorithms can be generally divided into two main systems such as PM drives [6]. Considering the finite amount of possible switching states in the converter ٤٧ unit, this type of control algorithm is also famous as "finite set model predictive control" (FS-MPC).
٤٨On the other hand, the second group can be considered as an extension of traditional field-oriented ٤٩ control of generator. In this group, the inner PI controllers are removed and replaced by predictive
٥٠controllers. Moreover, reverse model of generator is used to calculate appropriate reference voltages, and a
٥١modulator is usually used to generate the computed reference voltages [7].
٥٢Model predictive control has also been examined successfully in the case of multiphase generators [8].
٥٣Comparing to standard three-phase generators, multi-phase structure of a BLDC generator results in of system states a fault detection and isolation algorithm is developed in [14]. As the mathematical model
٦٨of BLDC generator is sufficiently well developed, EKF is ideally suited for the case of five-phase BLDC
٦٩generator applications.
٧٠In this paper, extended Kalman filter based predictive deadbeat control (EKF-PDC) is developed for ٧١ five-phase BLDC generator. Proposed controlling algorithm includes two main steps namely "current ٧٢ estimation step" and "voltage application step". EKF is developed for five-phase BLDC generator, and is
٧٣executed during "current estimation step" to reduce the effect of ...