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State estimation of induction machines may be a difficult problem, due to the non-linear behavior of theirs. For non-linear state estimation, the unscented Kalman filter (UKF) is a well-known extension of the linear Kalman filter. Operation of the UKF algorithm strongly depends on the process and measurement noise covariance parameters of the estimator. Determination of these parameters is not straightforward...
This paper presents the design of Unscented Kalman Filter (UKF) for estimation of state space variables of permanent magnet synchronous machine (PMSM). The UKF is shown together with the field oriented speed control. At first, the position and the speed of PMSM are measured, and UKF is used only for a load torque estimation. It is indicated how differences in sampling time of the speed and the current...
In this paper, an observer-based speed sensorless field oriented control (FOC) algorithm is presented for induction machines. The state observer is based on a new, detailed observer model which describes the machine with seven state variables, i.e. with seven equations. Since these equations are strongly non-linear, the applied observer algorithm is the unscented Kalman filter (UKF). Using the advantages...
Development of control algorithms for electrical machines may be a difficult procedure if functional safety, software quality, reusability and expandability come into scope. These properties might be required in both of research and industrial development projects. State of the art methods and tools like model-based design (MBD) and automated code generation may help to meet these requirements. In...
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