V
Valeriu Bostan
Researcher at Politehnica University of Bucharest
Publications - 22
Citations - 499
Valeriu Bostan is an academic researcher from Politehnica University of Bucharest. The author has contributed to research in topics: AC power & Induction motor. The author has an hindex of 8, co-authored 21 publications receiving 463 citations. Previous affiliations of Valeriu Bostan include University of Bucharest.
Papers
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Journal ArticleDOI
Improved current control strategy for power conditioners using sinusoidal signal integrators in synchronous reference frame
TL;DR: In this paper, a proportional-integral regulator using sinusoidal signal integrators (SSIs) is proposed for shunt type power conditioners to compensate current harmonics.
Proceedings ArticleDOI
General adaptation law for MRAS high performance sensorless induction motor drives
Giovanni Battista Griva,Francesco Profumo,Radu Bojoi,Valeriu Bostan,M. Cuius,Constantin Ilas +5 more
TL;DR: In this paper, a general adaptation law for sensorless vector control of induction motors using the model reference adaptive system (MRAS) approach with Luenberger observer is presented, which has been experimentally tested and compared with the classical adaptation mechanism at both low and high speed.
Journal ArticleDOI
Improved Mathematical Model of PMSM Taking Into Account Cogging Torque Oscillations
TL;DR: In this paper, an improved mathematical model of Permanent Magnet Synchronous Machine (PMSM) that takes into account the Cogging Torque (CT) oscillations that appear due to the mu...
Proceedings ArticleDOI
Design of current controllers for active power filters using naslin polynomial technique
TL;DR: In this article, a new method for tuning the resonant controllers also known as proportional sinusoidal-signal-integrator (P-SSI) controllers, based on Naslin polynomials theory, is proposed.
Proceedings ArticleDOI
Luenberger, Kalman and neural network observers for sensorless induction motor control
TL;DR: A comparison between the sensorless vector control schemes of the induction motor using the Luenberger observer, the Kalman filter and a neural network observer is presented.