P. Vranka

Politecnico di Torino, Torino, Piedmont, Italy

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Publications (3)0 Total impact

  • P. Vranka · G. Griva · F. Profumo
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    ABSTRACT: The aim of this paper is to show how the performance of a simple V-I flux estimator for field oriented (FO) controlled drives can be improved, simply by improving the quality of the input signals (voltages and currents) and eliminating the offset from the resulting flux signal, without using sophisticated mathematical methods such as Luenberger observers, Kalman filters or others. The proposed method requires almost no increase of the computation time in digital implementation, thus a cheap processor can be used
    No preview · Conference Paper · Jan 1998
  • G. Griva · C. Ilas · J.F. Eastham · F. Profumo · P. Vranka
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    ABSTRACT: This paper deals with some aspects concerning the implementation of a sensorless induction motor control for industry applications. The proposed control method uses an adaptive rotor flux observer and a suitable adaptation law for the speed estimation. It has been found that this method is superior to many other methods when the performance versus complexity criterion is considered. The adaptation law is obtained by a general one, valid for any induction motor parameter estimation. A comparison between the floating and the fixed point DSP implementation of the proposed method is presented. In fact, the appearance of new and powerful fixed point DSP microcontrollers makes the fixed point solution very attractive for many industrial applications, such as retrofits, conveyors control, and a lot of manufacturing process control. Different algorithm implementation issues, such as the online computation of the observer gain matrix and of the discrete motor model are discussed in this paper. Simulation and experimental results for the two cases (fixed and floating point DSP implementation) are shown
    No preview · Conference Paper · Sep 1997
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    C. Griva · F. Profumo · C. Ilas · R. Magureanu · P. Vranka
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    ABSTRACT: In this paper a unified approach to different schemes based on model reference adaptive systems (MRAS) for speed sensorless field oriented controlled (FOC) induction motor drives is presented. In the last few years several solutions belonging to this category have been proposed. They have different configurations and distinct adaptation mechanisms, properly chosen in each case. A new, general adaptation mechanism is presented in the paper. It is derived according to Popov hyperstability theory and is valid for any adaptive system belonging to this category, no matter what its configuration is. A general demonstration for the stability of these adaptive systems is given, using the Lyapunov stability theorem. This unitary approach allows an easier comparison and classification of different particular solutions. The paper focuses on two of the most used configurations. In the first solution the reference model is the motor and the adaptive one is a linear state observer, which, in particular, is an extended Luenberger observer (ELO). In the second solution, both models are rotor flux (or other quantities) estimators and this scheme is usually known as a model reference adaptive system (MRAS). The performance of these two schemes is analyzed starting from their configuration and then compared by simulations and experimental results
    Full-text · Conference Paper · Nov 1996